αAGIALPHACuriosity in your hands

TRANSFORMATIONAL INTELLIGENCE · A USEFUL FIRST STEP

Find your Alpha.
Build your SUCCESSOR Ω.

Compare two lists. See what needs attention. Turn scattered differences into an action plan, then keep a workspace you can use again.

No account, installation, wallet or API key. The example and your permitted CSV files run locally in your browser.

  • Free browser start
  • No wallet to plan
  • Save your workspace
YOUR NEXT CAPABILITY

From opportunity to earned advantage.

Public software. Frontier research. Mathematical exploration. Start with a valuable outcome, then develop the capability to pursue it.

  1. Discover a valuable opportunityDiscover
  2. Build and improve strategiesLevel 3
  3. Reframe the problemLevel 4
What you keepOne project history

Reviewed deliverables, strategies and lessons. Keep and improve what proves useful.

NEW FLAGSHIP · PUBLIC SIMULATION

Profitable work. Capability worth keeping.

Explore an ambitious engineering mission: the deliverable, matched human service, price, complete costs and available funds. Then test whether retaining a capability helps the next mission.

Explore the Flywheel

Free, without an account or wallet. Deterministic browser simulation; no models executed and no real revenue.

FOUNDATION / ORGANIZE INTELLIGENCE

AGI ALPHA: A Scalable Substrate for Intelligence Organizations

AGI ALPHA organizes intelligence. TRANSFORMATIONAL INTELLIGENCE changes the conditions of discovery.

A proposed, testable architecture and evaluation program for coordinated, governed, evidence-producing work across agents, jobs, validators, tools, memory, markets, settlement and capacity allocation.

Not a claim of achieved AGI, ASI, empirical state of the art, autonomous sovereignty, energy abundance or civilization-scale capability.

Read the foundational AGI ALPHA paper ↗ Read the announcement on X ↗ · TRANSFORMATIONAL INTELLIGENCE and the research series

RELATED ARCHITECTURE RESEARCH

Proposed designs and research doctrines, not claims of a fully implemented system, achieved general capability or commercial success.

ARCHITECTURE PAPER / CURRENT EDITION V1

NEURAL-SYMBOLIC SUCCESSOR Ω

Customer-Owned Mission Intelligence

A proposed portable mission institution with four distinct programs: WORLD maintains beliefs, POLICY proposes actions, PROOF records independently demonstrated claims, and AUTHORITY defines permitted actions.

Successors may inherit memory, provenance, failures, program lineage and operating history. Proof status and production authority start empty and must be earned anew.

Architecture and product constitution, not a claim that the complete system is implemented or that general autonomous capability has been achieved.

Read the current paper (v1 PDF) ↗ Read the v1 announcement on X ↗

Earlier edition (v0 PDF) · v0 announcement

RELATED ARCHITECTURE / SEALED WORK ORDERS

SUCCESSOR Ω × AGI JOBS

A proposed connection between mission-governed intelligence and sealed work orders that manufacture, test, operate and renew capabilities.

The paper connects institutional design with a work-order mechanism, not evidence of a fully deployed or commercially proven autonomous institution.

Read SUCCESSOR Ω × AGI JOBS (v2 PDF) ↗ Read the paper announcement on X ↗

RELATED ARCHITECTURE / TRAINING, PROOF AND ADMISSION

Gym, Specialist ASI & Successor Ω

Mission Gym supplies controlled, versioned, rights-cleared mission environments. Specialist ASI is an earned, mission-bounded designation requiring comparison against strong alternatives on fresh protected work. Successor Ω requires separate admission with scoped, expiring, revocable authority.

Training is not certification. Descendants may inherit memory, not authority. These are proposed institutional requirements, not a claim of achieved superiority or a deployed institution.

Read the Gym architecture paper (v2.1.0 PDF) ↗ Read the paper announcement on X ↗

FROM MONTREAL.AI

Read the featured thread on X ↗

THE RESEARCH

Better strategies. A different game. New capabilities.

Research manuscripts on changing the conditions of success, while preserving the purpose of the work.

RESEARCH MANUSCRIPT · BOUNDED COMPUTATION

Autonomous Enterprises — Build the Means of Building

Capability-Producing Computation and Exact Capital Requirements for Succession

A bounded certifying computation constructs a checked transform–convolution–inverse solver and studies exact capital and capability retention under declared concatenability assumptions. The finite examples compare shared construction with isolated tasks and show when cash-only pruning loses useful capability. Research constructions and exact models, not a new Fourier algorithm, physical deployment or realized commercial growth.

Read the paper: Autonomous Enterprises: Build the Means of BuildingEnglish PDF

LOCAL COMPANION · REJECTION-ONLY TRANSFER

Autonomous Enterprises — Activate. Evolve. Scale.

Reusable Launch Kits with Rejection-Only Improvement Transfer

Three deterministic local offerings study reusable launch kits and transfer of rejection experience while leaving full acceptance checks unchanged. Retained limits include a conventional ordering that wins one comparison, a rejected second learned update and a four-worker run slower than two workers. A bounded local study, not general recursive self-improvement or evidence of three paying businesses.

Read the paper: Autonomous Enterprises: Activate. Evolve. Scale.English PDF

INTEGRATION SPECIFICATION · MODELED EXPERIMENT

Autonomous Enterprises — SUCCESSOR Ω Harness

Constructing and Financing Reusable Productive Capability

A source-grounded integration specification and bounded interval-measurement experiment compare independent setup, ordinary harness reuse and instrument reuse, including verification, failed transfer and recovery. The manuscript distinguishes deployed inventory, an open Harness candidate, replayed examples and new simulations. It does not establish autonomous incorporation, observed demand, investment performance or approved mainnet execution. The Harness implementation remains separately tracked in unresolved PR #4863; this paper listing does not claim that it has shipped.

Read the paper: Autonomous Enterprises: Activate. Evolve. Scale. — SUCCESSOR Ω HarnessEnglish PDF

COMPUTATIONAL STUDY · SIMULATED INSTRUMENTS

Autonomous Enterprises — Foundry v2

SUCCESSOR Ω Harness · Powered by TRANSFORMATIONAL INTELLIGENCE ∞. · A Foundry of Discovery Instruments

A simulated thermal-fluid foundry constructs fixtures, a calibration station and a qualified research instrument, then a new calorimetry method and a distinct simulated successor. A retained failure: the 4.9477% predicted/observed heat difference passes the 5% runtime rule, while the calorimeter has 8.6964% error against reference-model true heat. Conventional engineering ties useful accuracy with 384 versus 672 readings; a centralized lab is CAD 460 cheaper. Participant withdrawal and underutilization fail in the tested economic cases. Finite search, modeled economics and Python contract checks; physical construction and deployment NOT RUN. Reproduction requires the full research companion; standalone TeX requires the full LaTeX source ZIP.

Read the paper: 🌌⚙️ AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — SUCCESSOR Ω Harness — Powered by TRANSFORMATIONAL INTELLIGENCE ∞.English PDF Read the edition and resources: 🌌⚙️ AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — SUCCESSOR Ω Harness — Powered by TRANSFORMATIONAL INTELLIGENCE ∞. Explore the interactive foundry: 🌌⚙️ AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — SUCCESSOR Ω Harness — Powered by TRANSFORMATIONAL INTELLIGENCE ∞. Download the research companion: 🌌⚙️ AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — SUCCESSOR Ω Harness — Powered by TRANSFORMATIONAL INTELLIGENCE ∞. View source and evidence: 🌌⚙️ AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — SUCCESSOR Ω Harness — Powered by TRANSFORMATIONAL INTELLIGENCE ∞.

RESEARCH EDITION 01 · CAPABILITY INHERITANCE

Autonomous Enterprises — Capability Inheritance

Capability inheritance, complete counted cost, and a constructive thermal-measurement counterexample.

Retained executable capabilities serve 48 mathematical tasks using 63,196 counted work units versus 915,136 for rebuilding, but the supplied expert uses 5,760. Inherited successor qualification loses 7,918 versus 2,030 directly. A separate simulated thermal witness gives a conditional 1.8862% bound. Local-EVM and native-worker evidence remains separate from unfinished end-to-end thermal integration; physical validity and full monetary, human and energy costs are unknown. No measured profit is established. The 25-page manuscript is preserved; reproducible TeX requires its complete source package.

Read the paper: Autonomous Enterprises: Activate. Evolve. Scale. — SUCCESSOR Ω HarnessEnglish PDF Read the edition and resources: Autonomous Enterprises: Activate. Evolve. Scale. — SUCCESSOR Ω Harness

RESEARCH EDITION · SYNTHETIC DECISION EXPERIMENTS

Autonomous Enterprises — The Discoverability Compiler

Decision-separating measurements and scope-checked successors

A bounded compiler constructs nuisance-canceling measurement programs and checks whether they separate an authorized decision. Conventional baselines tie development acquisition costs; an adaptive control wins. Reuse reduces counted construction work, while timing is unstable and centralized execution remains faster. The ≤US$100 total-cost to US$10,000 realizable incremental-value challenge is UNPROVEN: no executable offer or customer receipt exists, and complete cost is unknown. This preserved 24-page amended paper does not qualify its open-review runnable experience or establish physical validation or installed enterprise integration. Reproducible TeX requires the complete research source.

Read the paper: AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — The Discoverability CompilerEnglish PDF Read the edition and resources: AUTONOMOUS ENTERPRISES: ACTIVATE. EVOLVE. SCALE. — The Discoverability Compiler

CONSTRUCT THE EXPERIMENT

Out-Learn 📚

Change What You Need to Know

Studies how to construct measurement protocols and learn reusable calibration, with error guarantees under declared drift and measurement-error assumptions in exact synthetic studies.

Read the paper: Out-Learn 📚English PDF

RETHINK THE REPRESENTATION

Out-Think 🧠

Transformational Intelligence for Inventing the Space of Reasoning

Studies executable reasoning representations that preserve required answers and operations, and when to replace rather than refine inherited internal codes, in exact finite models.

Read the paper: Out-Think 🧠English PDF

MAKE CHANGE POSSIBLE

Out-Design 🎨

Creating the Freedom to Transform

Studies equivalent implementations that preserve required services and release usable capacity for reconfiguration and new capabilities, with checked constructions in finite executable models.

Read the paper: Out-Design 🎨English PDF

MAKE PROGRESS LAST

Out-Execute ⚡

Preserve progress as tasks change through reusable execution capabilities and independently checked boundary contracts, demonstrated in finite synthetic studies.

Read the paper: Out-ExecuteEnglish PDF

BUILD WHAT COMES NEXT

Out-Evolve ♾️

A proposed architecture for building experimentation and production capabilities that make further discoveries and successor capabilities possible.

Read the paper: Out-EvolveEnglish PDF

CAPABILITY INHERITANCE · EXECUTABLE EVIDENCE

TRANSFORMATIONAL AUTONOMOUS ENTERPRISES

SUCCESSOR Ω Harness — Mission-Relative Revalidation for Capability Inheritance Across Four Execution Systems

A finite graph-capability study connects four source runtimes and five local-EVM contracts: fresh mission checks remain, repeated qualification work falls, direct-specialist wins and unproven economic value are retained. The experimental companion's source and assembly guidance do not establish installed or deployed acceptance.

Read the paper: TRANSFORMATIONAL AUTONOMOUS ENTERPRISESEnglish PDF Download standalone TeX: TRANSFORMATIONAL AUTONOMOUS ENTERPRISES Current corrected companion guide and helper: TRANSFORMATIONAL AUTONOMOUS ENTERPRISES Historical experimental companion source and assembly: TRANSFORMATIONAL AUTONOMOUS ENTERPRISES

RESEARCH EDITION 01 · SYNTHETIC SPECTROSCOPY

The Possibility Foundry

From Autonomous Capability Synthesis to Measurable Expansion of Economic Opportunity · Writer #5 / Research edition 01

A bounded 64-channel synthetic-spectroscopy study constructs a calibrated instrument from a finite 60-plan grammar. Under the declared resource cap, 1,678/2,048 fresh missions pass quality and cost. The full scanner has better quality; both supplied software builders use less construction work than the foundry. Transfer succeeds on 204/512 tasks; narrow-line stress passes 0/128. A temporal child passes 128/128 with retained parent capital, but 0/128 with fully loaded de novo cost; a shorter conventional construction also fits its cap. Two same-seed runs are not independent replication. Retained Alpha workbench/Jobs compiler source evidence does not establish installed four-repository, physical or commercial acceptance. Full monetary and human costs are unknown; the $100-to-$10,000 target is NOT ESTABLISHED. This original 21-page paper is preserved; compiling its TeX requires the complete archive bibliography and figures.

Read the paper: The Possibility Foundry: Autonomous Enterprises That Invent Their Next CapabilityEnglish PDF Download complete research source ZIP: The Possibility Foundry: Autonomous Enterprises That Invent Their Next Capability Download visual signature (not cryptographic): The Possibility Foundry: Autonomous Enterprises That Invent Their Next Capability View source and evidence: The Possibility Foundry: Autonomous Enterprises That Invent Their Next Capability

REUSABLE SCIENTIFIC CAPABILITY

SUCCESSOR Ω HARNESS

Make Every Mission Build What Comes Next

A 28-page simulated detector study with a runnable research companion: retained construction ties conventional caching, while expert construction uses fewer counted rational calls. Physical validity, settlement and profit are not established.

Read the paper: SUCCESSOR Ω HARNESS — Make Every Mission Build What Comes NextEnglish PDF Download the research companion: SUCCESSOR Ω HARNESS — Make Every Mission Build What Comes Next Download complete research source ZIP: SUCCESSOR Ω HARNESS — Make Every Mission Build What Comes Next View source and evidence: SUCCESSOR Ω HARNESS — Make Every Mission Build What Comes Next

REUSABLE CAPABILITY · ACCELERATION STUDY

AGI ALPHA FLYWHEEL

From Completed Work to Compounding Capability · Edition 02

An 18-page bounded study of retained executable component bases. All four workflows qualify 864/864 tasks; conventional caching ties the flywheel, the authored expert costs less, and none of eight streams demonstrates sustained acceleration. Computational counts do not establish commercial value.

Read the paper: AGI ALPHA FLYWHEEL: From Completed Work to Compounding CapabilityEnglish PDF

THE ECONOMICS OF ACCEPTED DIGITAL WORK

AGI ALPHA FLYWHEEL: The Economics of Autonomous Work

A bounded exact-reconciliation study reports 36/36 accepted fresh jobs and 0.301-second median turnaround. Official labor data support conditional human-work economics; complete costs, remaining employer attention and a matched human trial are unmeasured.

Read the paper: AGI ALPHA FLYWHEEL: The Economics of Autonomous WorkEnglish PDF Historical experimental companion source and assembly: AGI ALPHA FLYWHEEL: The Economics of Autonomous Work

USEFUL WORK AND VERIFIED CAPABILITY CONSTRUCTION

AGI ALPHA FLYWHEEL

From Useful Work to Reusable Productive Capability

A preregistered bounded study accepts 42/42 fresh jobs across seven digital-work families and records actual reusable-capability invocation. Tested inheritance candidates establish neither net savings nor self-acceleration. Official labor data support conditional adoption economics; full Agent cost and employer attention remain unmeasured.

Read the paper: AGI ALPHA FLYWHEEL: From Useful Work to Reusable Productive CapabilityEnglish PDF Historical experimental companion source and assembly: AGI ALPHA FLYWHEEL: From Useful Work to Reusable Productive Capability

COMPLETE OPERATIONAL COST AND ACCEPTED WORK

AGI ALPHA FLYWHEEL

Complete Economics of Accepted Work

A separately frozen, market-data-grounded operational comparison prices delivery, failures, review, setup and capability upkeep against traditional non-AI work. The primary 30-minute office scenario does not establish an economic win at the modeled expected-use capacity limit. Conditional thresholds, complete-demand fallback and unvalidated setup scheduling remain explicit; no deployed-service cost or new human trial is claimed.

Read the paper: AGI ALPHA FLYWHEEL: Complete Economics of Accepted WorkEnglish PDF Historical experimental companion source and assembly: AGI ALPHA FLYWHEEL: Complete Economics of Accepted Work

PRODUCTION AND REINVESTMENT

AGI ALPHA FLYWHEEL: The Productive Capital Engine

From Valuable Work to Expanding Productive Capability

A frozen study connects useful local work to a conserved economic model; conditional service margins are modeled, while the constructed child does not outperform conventional reuse.

Read the paper: AGI ALPHA FLYWHEEL: The Productive Capital EngineEnglish PDF

COLLECTED SURPLUS AND BOUNDED CAPABILITY INVESTMENT

AGI ALPHA FLYWHEEL

The Economic Engine

A separately preregistered financial simulation connects useful recorded work, complete business costs, collected proceeds, reserves and bounded capability investment. It preserves unfavorable paths, idle allocations and failed construction, with distinct source-inspected USDC and AGIALPHA settlement routes. Simulated gains, token realization and customer value remain conditional; no live revenue, transaction or self-acceleration is demonstrated.

Read the paper: AGI ALPHA FLYWHEEL: The Economic EngineEnglish PDF Historical experimental companion source and assembly: AGI ALPHA FLYWHEEL: The Economic Engine

EXECUTABLE CAPABILITY CONSTRUCTION

BUILD THE NEXT ADVANTAGE

From Useful Work to Expanding Productive Capability

Example-derived quote adapters qualify on 96 fresh missions. Active selection matches the learned recipe and LLM-assisted constructor; complete costs and simulated financing keep the stronger incumbent and expose the limits.

Read the paper: AGI ALPHA FLYWHEEL: Build the Next AdvantageEnglish PDF

AUTOMATED WORK, COMPLETE COSTS AND CAPABILITY TRANSFER

AGI ALPHA FLYWHEEL: The Autonomous Work Economy

From Useful Outcomes to Expanding Productive Capability

An independent bounded study delivers 16 local artifacts across four workflow families, retains eight expected refusals, and tests a successor on eight later quote cases. Complete costs and reinvestment remain conditional models; customer payments, full authenticated execution and self-acceleration are not established.

Read the paper: AGI ALPHA FLYWHEEL: The Autonomous Work EconomyEnglish PDF

USEFUL CAPABILITY AND ECONOMIC ADMISSION

THE ADVANTAGE THAT FUNDS THE NEXT

Useful Work → Productive Surplus → Greater Capability

A versioned release-inventory intake capability serves the actual Alpha Workbench. Three strong methods correctly complete 16 fresh comparison requests and 64 representations each. Complete costs and attention savings remain unmeasured; no material incremental advantage is established. Financing scenarios bind the exact tested asset, preserve adverse outcomes and leave actual economic admission on HOLD.

Read the paper: AGI ALPHA FLYWHEEL: The Advantage That Funds the NextEnglish PDF Historical experimental companion source and assembly: AGI ALPHA FLYWHEEL: The Advantage That Funds the Next

MEASURED DISCOVERY · HOLD

Build an Advantage That Repays Its Cost — The Investment Gate

Measured discovery and an unselected investment

Nine scoped internal requests and eighteen evaluations with overlapping inputs produced eight complete measured local paths, not eight authenticated native missions. One scope retained its native artifact-policy refusal. No productive asset was selected or constructed and no untouched confirmation trial was run. Full monetary cost, repayment and positive incremental economics remain unestablished. DISCOVERY/HOLD.

Read the paper: Build an Advantage That Repays Its Cost: The Investment GateEnglish PDF

DEPENDENCY DECISIONS · ECONOMIC HOLD

The Next Upgrade

Consumer-specific dependency decisions and an unproven investment

A consumer-specific dependency assessment accepted nine of twelve custom-method scopes versus twelve of twelve for the conventional comparator. The custom method was rejected; local task support and reuse do not establish cheaper capability construction or commercial success. Complete monetary costs, repayment and sustained acceleration remain unestablished. Economic HOLD.

Read the paper: The Next Upgrade: An AGI ALPHA Business Case for Consumer-Specific Dependency DecisionsEnglish PDF Historical experimental companion source and assembly: The Next Upgrade: An AGI ALPHA Business Case for Consumer-Specific Dependency Decisions

SIMULATED ECONOMICS · CONDITIONAL

Profitable Work First. Compounding Capability When Worthwhile.

Conditional simulated commercial economics; Alpha evaluated separately

Under declared assumptions, a simulated coordination-mechanism foundry produces positive mean Beta-only surplus, including a stricter useful-receipt-only sensitivity. These are conditional model results, not actual customer sales or qualified frontier-model delivery. Primary confirmation does not establish a positive additional enterprise benefit from retained Alpha or network sharing; capability compounding remains unproven.

Read the paper: Profitable Work First. Compounding Capability When Worthwhile.English PDF Historical experimental companion source and assembly: Profitable Work First. Compounding Capability When Worthwhile.

EXECUTED LIFECYCLE · MODELED ECONOMICS

When Paid Work Teaches the Network

Profitable delivery. Selective Alpha. Expanding productive possibility.

Competent Beta is profitable under the modeled primary markets, with incomplete service-quality qualification. Selected retention policies keep nothing; a cheaper-retention diagnostic supports useful peer reuse but remains uneconomic as a complete program. This is not demonstrated profitable autonomy or a positive network flywheel.

Read the paper: When Paid Work Teaches the NetworkEnglish PDF Read the edition and resources: When Paid Work Teaches the Network

EXECUTABLE RESEARCH · LEARNING, TRANSFER AND ECONOMICS

AGI ALPHA FLYWHEEL — The Network That Learns to Invent

Profitable Work, Experience-Trained Specialists and Shared Alpha

A numerical learning system constructed by the research team develops a reduced basis from thermal work and tests its transfer to fresh diffusion and sensor-design missions. Mean raw transfer error falls 26.3-fold, but neither raw version passes any of 64 recipient cases; corrected solutions pass. The competent generalist matches the composition’s identification success. Under explicit cost and demand assumptions, modeled Beta delivery can be profitable while optional retention is rejected. Local numerical evidence and simulated economics, not customer sales, autonomous invention, live ENS authentication or specialist superintelligence.

Read the paper: The Network That Learns to InventEnglish PDF Read the edition and resources: The Network That Learns to Invent Historical experimental companion source and assembly: The Network That Learns to Invent Download complete research source ZIP: The Network That Learns to Invent View source and evidence: The Network That Learns to Invent

English originals. Research proposals and bounded studies, not claims of general autonomous capability or physical deployment.

ONE PROJECT. EXPLICIT CHOICES. RETAINED HISTORY.

From opportunity to useful capability.

Define the outcome, prepare bounded Computer Use work and review what was actually delivered. Keep strategies, attempts and lessons in the same project as you continue through Alpha, Jobs and Fleet.

Level 3 · Meta-strategic intelligence: discover, test, combine and improve strategies themselves. Level 4 · Transformational intelligence: recognize a restrictive formulation and investigate a fundamentally different game to play.

The browser prepares native missions and unfunded work, and preserves checked historical returns. Computer execution requires a configured model and disposable Chromium runner. Independent qualification and settlement remain separate requirements.

Maintained engineering examples are available separately. Explore local catalog tools ↗

CHOOSE THE PAYMENT ROUTE

USDC · $AGIALPHA

AGIJobManager uses USDC. Alpha and AGI Jobs v0 use $AGIALPHA. Each keeps its own pricing, admission and settlement rules; no automatic conversion occurs.

Fleet receives an explicitly selected local task and returns execution and internal checking evidence. A returned file grants no execution permission.

ALPHA AGENT + AGI JOBS

From a useful idea to accepted work.

Alpha helps plan and produce work. AGI Jobs provides rules for commissioning, reviewing and settling it. Explore how a carefully connected workflow can bring both strengths together.

ONE SHARED TOKEN · ETHEREUM MAINNET

$AGIALPHA

0xA61a3B3a130a9c20768EEBF97E21515A6046a1fA

5 Alpha + 24 AGI Jobs instances in the 11–12 October 2026 public records.

Read the linked deployment evidence and readiness notes. A shared token does not create an automatic bridge or open live job intake.

NOVA-SEED STUDIO

Give your next idea a future.

Shape a project, check its exact work plan and protect it with encrypted recovery. Keep the same history as you connect execution, inspect results and consider the next cycle.

Local preparation needs no wallet or payment. New minting, funding and commitments are blocked on the archived Mainnet deployment. External execution, review and settlement have separate prerequisites.

A PROJECT YOU CAN KEEP

  1. Plan exact, verifiable work
  2. Encrypt, download and recover
  3. Review evidence and continue deliberately

Download recovery before leaving Studio. Keep the capsule passphrase separately; never use your wallet recovery phrase.

Simple from the first step

Your pace. Three easy steps.

Choose a result that matters. Improve the approach. Keep the work and what you learned.

  1. Define the useful result

    Choose a consequential opportunity in software, research or mathematics. State who benefits and what a useful deliverable must achieve.

  2. Find a better way to work

    Level 3: test and combine strategies. Level 4: challenge an unnecessary restriction while preserving the required outcome. Review the real deliverable before accepting an attempt.

  3. Keep what you build

    Save your workspace with its results, strategies, reviews and history. Reopen it, preserve what worked and prepare the next improvement.

A little reassurance

A few things you may be wondering.

Open any question to read the answer.

Is the Alpha flagship free to try?

Opportunity planning, mission preparation and workspace downloads are free, without an account or wallet. Native Computer Use execution requires an operator’s configured runner and model, with separate provider and operating costs. Maintained local engineering examples remain available.

Do I need to install anything?

Nothing to install for browser planning, the catalog example, personal lab or simple planner. Native Computer Use execution requires a configured model and container runner. Your saved workspace remains an HTML file you can open offline.

Where do my inputs and results go?

Browser planning and catalog processing stay in your browser. Native Computer Use sends the approved work surface and screenshots to the operator-selected model. Use public, non-personal inputs. Save your complete workspace before closing and after changes; exports include your supplied inputs.

What advantage has this actually proved?

A proposed capability, generated patch or mathematical argument is a candidate. Inspect its actual work, test the important claims and measure full costs before claiming advantage. Independent proof, Specialist status, income and operational permission require their own evidence.

Can I make it easier to read?

Yes. Choose Larger text at the top or use your browser zoom. English and French are available on the homepage, in the Alpha flagship, in your personal lab and in the simple planner.

YOUR NEXT DISCOVERY STARTS HERE

Keep the result. Improve the method.

Discover valuable work. Build a capability to deliver it. Improve the strategy. Change the game.

Start the flagship Explore the personal Ω lab Make my first plan

SELECTED READING

The ideas behind the work.

Explore opportunities, compare improvements and retain useful discoveries.

Essays by Vincent Boucher · English originals on LinkedIn. Some describe earlier versions; current guides explain setup, payments and availability. LinkedIn may ask you to sign in.

Alpha and AGIJobsv0 share a $AGIALPHA ecosystem. AGIJobManager provides the separate USDC route. Each execution and settlement connection needs its own configuration and evidence.

Reading notes and version context

For the curious

Explore further, at your own pace.

There is more here when you want it: planning tools, experiments and the original research.

Start with the Alpha flagship above, explore the personal lab or try the simple planner. The advanced tools and research below are in English; some offer their own language options and may need technical knowledge.

META-AGENTIC α–AGI · OPEN RESEARCH

Seize the Alpha.
Transform
the world.

A laboratory for the next frontier of intelligence. Discover opportunities. Orchestrate useful work. Follow the value through the entire loop.

New here? Follow a simple guided example in English or French. No account, wallet, payment or installation needed.

αINSIGHT → IMPACT → INSIGHT

Identify · Give the mission a goal and bounded, explicit inputs.

06 connected Ascension stages24 original demos + 2 resources04 native mission workflowsWhat works & its limits ↗

BUILD · VERIFY · CARRY KNOWLEDGE FORWARD

SUCCESSOR Ω

Construct a bounded capability and inspect its evidence. Run a local rehearsal in English or French, then exchange requests and results with your native agent. Knowledge carries forward; permissions require fresh review.

NEW / THE COMPOUNDING LAB · v1.46.1

Proof, carried
forward.

Learn once. Freeze the capability. Test a different future. Inspect real predictions, expose failure, count the costs, and take the complete evidence with you.

Begin the experiment ↗

NOVA-SEEDS / PROOF BLOOM

Potential is a seed.
Proof is the bloom.

Five guided experiences. One complete path from unsupported claim to executable jobs, reviewed evidence and the next invention.

Enter the Proof Bloom ↗

Current Mainnet record · five verified contract addresses. Read-only evidence recorded on 18 October 2026. Operational approval remains a separate step.

THE WHITE PAPER, MADE EXPLORABLE

One idea.
An entire ecosystem.

Take a real computational journey through the original vision. Each decision changes the plan. Every result can be inspected.

Editable scenario data · actual portfolio and scheduling algorithms · real encryption · clearly labeled economic simulations

Methods & evidence ↗

NEW / THE INSIGHT ATLAS

Possibility, on a grand scale.
Evidence, at every step.

Enter the Insight Atlas ↗

Three connected experiences · editable inputs · exact calculations · replayable evidence · no account or API key

THE GOVERNANCE OBSERVATORY

Don’t just read
the theory.
Challenge it.

Move the assumptions. Watch strategies compete. Test the risk budget and the eight-day governance gate.

Enter the observatory ↗

01 / MAKE SOMETHING USEFUL

Your mission starts here.

Try the example. Replace it with your own inputs.
Every result comes with its method and limits.

CHOOSE A WORKFLOW

Exact bounded search

Advanced · edit native mission JSON

Ready. The example uses sample planning units; edit them for your problem.

Mission memory 0 saved

Only missions you explicitly save stay in this browser. Reload saved inputs to improve a decision. Export important work before clearing browser data.

02 / EXPLORE LOCAL INTELLIGENCE

A small model.
On your machine.

Try actual GPT-2 text generation in this browser. The model downloads only when you ask, then generates locally. It is a text-completion research baseline; it can be wrong and is not a reasoning assistant.

Open the full Insight simulation studio ↗
LOCAL MODEL LABGPT-2 · q8 · WASM

First use downloads about 128 MB of model weights plus the runtime. Prompts stay on this device.

Your model output will appear here.

03 / BUILD THE MEANS OF DISCOVERY

What could your next capability make possible?

Start with a working browser workspace. Explore the research behind capabilities that equip their successors. Keep the result, the evidence and the limits in view.

TRY THE CURRENT SYSTEM

Find an opportunity. Construct a capability. Keep what you learn.

These live browser tools are experimental. Planning and synthetic studies are not proof of autonomous profit or physical deployment.

01 / LIVE WORKSPACE

Find your Alpha

Explore a consequential opportunity and ask which new capability could make a family of valuable missions possible.

Open Discovery ↗
02 / LIVE WORKSPACE

Build your SUCCESSOR Ω

Develop a strategy, prepare bounded work and keep attempts, reviews and lessons in one project. Native execution needs a configured model and runner.

Open the capability studio ↗
03 / LIVE SYNTHETIC LAB

Make the next mission inherit more

Inspect the experimental enterprise's capability construction, comparisons and retained evidence. Count the work before claiming that reuse pays.

Open the enterprise lab ↗

THREE RESEARCH JOURNEYS / READ THE PAPERS

Beyond one answer: build what enables the next discovery.

Published computational studies, not hosted interactive experiences. Each paper preserves its baselines, failure cases and unvalidated claims.

RESEARCH / 33-PAGE PDF

A foundry of discovery instruments

Configurable fixtures help construct a calibration station, an instrument and a distinct successor module. Follow the simulated construction, including the metrology failure it exposes.

Read the Foundry study ↗
RESEARCH / 25-PAGE PDF

Achievements that become capabilities

Carry executable assets into a different requirement. See where inheritance saves rebuilding, where an expert remains cheaper, and where successor qualification costs more than starting directly.

Read Capability Inheritance ↗
RESEARCH / 24-PAGE PDF

Construct the conditions of discovery

Explore a discoverability compiler in finite computational models, with conventional baselines and a checked successor. Commercial returns and open-ended discovery remain unproven.

Read Discoverability Compiler ↗

PRACTICAL PLANNERS / PRESERVED AND AVAILABLE

Bring your constraints. Compare the trade-offs.

Eleven editable planning workspaces remain available below. Their supplied scenarios illustrate bounded decisions, not deployed autonomous businesses.

01 / Build a business

Ω-Lattice capital committee

Which investments fit a $1.2M budget and 500 staff days?

Investment slate · cash-flow model · downside sensitivityOpen workspace

02 / Build a business

Invention to operating value

Which inventions justify the cost of developing and operating them?

Development portfolio · prerequisite map · verification jobsOpen workspace

03 / Run operations

Supplier resilience desk

How should 60 batches be sourced when no supplier may exceed 45%?

Order allocation · landed costs · supplier-outage stress testOpen workspace

04 / Run operations

Factory delivery control

Can seven customer orders share four resources and meet the delivery window?

Resource-by-hour schedule · lateness report · priority orderOpen workspace

05 / Run operations

Product launch room

What delivery order fits a shared design, engineering and QA team?

Launch sequence · resource calendar · bottleneck analysisOpen workspace

06 / Run operations

Demand & replenishment desk

How much stock should be ordered for a two-week supplier lead time?

Holdout evaluation · replenishment quantity · demand stress testOpen workspace

07 / Run operations

Service staffing & backlog desk

Which shifts need extra staff, what will they cost, and can the backlog be cleared?

Shift-by-shift staffing · coverage caps · backlog flow · incremental costOpen workspace

08 / Run operations

Microgrid dispatch console

When should a battery charge while serving a facility across peak tariffs?

24-hour dispatch · energy balance · tariff cost comparisonOpen workspace

09 / Prove a claim

Proof Debt → AGI Jobs

Which claims survive the evidence, and what exactly must be proved next?

Evidence docket · assigned proof backlog · acceptance criteriaOpen workspace

10 / Prove a claim

Nova-Seeds pilot gate

Is a promising capability ready for an independently reviewed pilot?

Promotion hold reasons · proof jobs · attributable evidence docketOpen workspace

11 / Prove a claim

Second-order agency trial

Does redesigning the review pipeline improve outcomes after all stated costs?

Frozen selection · confusion matrices · costed held-out comparisonOpen workspace

EARLIER DEMOS AND PLANNING EXAMPLES

Explore the foundations. Keep your familiar starting points.

Earlier names and links remain available below. Some examples open shared, bounded planning workspaces; they are not separate deployed autonomous enterprises. The research implementations and guides remain linked inside. Choose a demo and run it locally.

AI-GA meta-evolution

AI-GA meta-evolution

Invention to operating value: Which inventions justify the cost of developing and operating them? Development portfolio · prerequisite map · verification jobs

Open practical workspace ↗
Business v2

Business v2

Invention to operating value: Which inventions justify the cost of developing and operating them? Development portfolio · prerequisite map · verification jobs

Open practical workspace ↗
Business 3 Enterprise Studio

Business 3 Enterprise Studio

Reproducible planning: Select a constrained enterprise portfolio, stress the downside and export reviewable Ascension jobs.

Open practical workspace ↗
Business v1

Business v1

Ω-Lattice capital committee: Which investments fit a $1.2M budget and 500 staff days? Investment slate · cash-flow model · downside sensitivity

Open practical workspace ↗
Insight Discovery Workbench

Insight Discovery Workbench

Local evidence review: Screen cross-sector hypotheses, allocate review time and export input-bound verification jobs and plaintext Nova-Seed drafts.

Open practical workspace ↗
Insight v1

Insight v1

Browser + simulation: Explores scenarios and Pareto search; optional browser GPT-2 performs real local text completion.

Open practical workspace ↗
Marketplace

Marketplace

Supplier resilience desk: How should 60 batches be sourced when no supplier may exceed 45%? Order allocation · landed costs · supplier-outage stress test

Open practical workspace ↗
ASI world model

ASI world model

Factory delivery control: Can seven customer orders share four resources and meet the delivery window? Resource-by-hour schedule · lateness report · priority order

Open practical workspace ↗
Super Planner

Super Planner

Factory delivery control: Can seven customer orders share four resources and meet the delivery window? Resource-by-hour schedule · lateness report · priority order

Open practical workspace ↗
Cross-industry discovery

Cross-industry discovery

Ω-Lattice capital committee: Which investments fit a $1.2M budget and 500 staff days? Investment slate · cash-flow model · downside sensitivity

Open practical workspace ↗
Era of Experience · Learning Lab

Era of Experience · Learning Lab

Offline learning lab: Learns a bounded policy from synthetic outcomes, tests it against a frozen baseline, and exports reviewable evidence.

Open practical workspace ↗
Finance Alpha Research Terminal

Finance Alpha Research Terminal

Reproducible paper research: Inspect next-open fills, cash, costs and risk decisions; compare strategies and replay every reported result.

Open practical workspace ↗
GPT-2 CLI

GPT-2 CLI

Proof Debt → AGI Jobs: Which claims survive the evidence, and what exactly must be proved next? Evidence docket · assigned proof backlog · acceptance criteria

Open practical workspace ↗
Macro Sentinel

Macro Sentinel

Demand & replenishment desk: How much stock should be ordered for a two-week supplier lead time? Holdout evaluation · replenishment quantity · demand stress test

Open practical workspace ↗
Meta-Agentic v1

Meta-Agentic v1

Second-order agency trial: Does redesigning the review pipeline improve outcomes after all stated costs? Frozen selection · confusion matrices · costed held-out comparison

Open practical workspace ↗
Meta-Agentic v2

Meta-Agentic v2

Second-order agency trial: Does redesigning the review pipeline improve outcomes after all stated costs? Frozen selection · confusion matrices · costed held-out comparison

Open practical workspace ↗
Meta-Agentic AGI v3 Curriculum Lab

Meta-Agentic AGI v3 Curriculum Lab

Reproducible program induction: Generate tasks, evolve bounded solver configurations and review a frozen candidate on separate tasks.

Open practical workspace ↗
Meta-Agentic Tree Search · Search Lab

Meta-Agentic Tree Search · Search Lab

Offline search lab: Explore competing workflow rewrites, resource schedules, held-out review gates and an exhaustive benchmark.

Open practical workspace ↗
MuZero planning

MuZero planning

Research planning: Train a small neural model and compare learned-model search with measured baselines.

Open practical workspace ↗
MuZero × MCTS × LLM

MuZero × MCTS × LLM

Research training: Retrieve cited evidence, compare optional local-model advice with trained search, and measure simulator outcomes.

Open practical workspace ↗
OMNI smart city

OMNI smart city

Microgrid dispatch console: When should a battery charge while serving a facility across peak tariffs? 24-hour dispatch · energy balance · tariff cost comparison

Open practical workspace ↗
Presentation assets

Presentation assets

Nova-Seeds pilot gate: Is a promising capability ready for an independently reviewed pilot? Promotion hold reasons · proof jobs · attributable evidence docket

Open practical workspace ↗
Repo-Healer

Repo-Healer

Product launch room: What delivery order fits a shared design, engineering and QA team? Launch sequence · resource calendar · bottleneck analysis

Open practical workspace ↗
Governance Workbench

Governance Workbench

Offline governance review: Inspect nine proposal gates and export reproducible evidence and validator jobs.

Open practical workspace ↗
Sovereign Workbench

Sovereign Workbench

Signed, review-gated workflow: Choose a feasible portfolio, schedule approved work, and produce an attributable evidence brief.

Open practical workspace ↗
Shared demo utilities

Shared demo utilities

Proof Debt → AGI Jobs: Which claims survive the evidence, and what exactly must be proved next? Evidence docket · assigned proof backlog · acceptance criteria

Open practical workspace ↗

04 / TAKE THE NEXT STEP

Make it your agent.

Keep browser exploration light.
Move reviewed work to a persistent, controlled runtime.

01

Install the verified release

Download the wheel, installer, locked dependencies and checksums from the same release. Python 3.11–3.13 is supported.

Get the release ↗
03

Close the loop with confidence

Import your downloaded mission in the console. Execute it, inspect evidence and approve a signed result. Configure models, isolated coding and wallet identity deliberately.

$AGIALPHA receipts connect approved work to recorded value. The agent checks payments and records reinvestment earmarks. Spending stays under your control.

Identity & payment setup ↗
Verify a signed result from your agent

Check an exported agent result here, without uploading it. Obtain the agent’s public key through a trusted channel; copying a key from an unknown file does not establish identity.

Supports v1.4.0 exports. Verification does not establish the truth of sources or mainnet settlement.

THE ORIGINAL VISION, KEPT IN VIEW

Ambitious by design.
Accountable in use.

Identify → Learn → Think → Design → Strategise → Execute. The flywheel connects evidence, useful work, human review and memory. The original diagrams, research, examples and historical implementations remain available.

This release provides bounded tools toward that vision. AGI, autonomous profit and open-ended self-improvement remain aspirations, not demonstrated capabilities.

Read the original vision & flywheels ↗

Know what you are running.

Capability & boundary matrix ↗Demo and browser test evidence ↗Agent acceptance evidence ↗Workspace guide, privacy & recovery ↗Live acceptance checks ↗

CANONICAL $AGIALPHA · ETHEREUM · 18 DECIMALS

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Alpha and AGIJobsv0 share the $AGIALPHA ecosystem. AGIJobManager provides the separate USDC route.