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Explain Laxmi research ambition and staged goals

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Clarify the long-term software world-model goal while retaining the experimental v0.1.1 claim boundary. Update SHA256SUMS for the model card; all artifacts remain unchanged.

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  1. README.md +12 -0
  2. SHA256SUMS +1 -1
README.md CHANGED
@@ -21,6 +21,18 @@ Laxmi investigates whether observed software state, history, an action and a pro
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  > Controller weights and runtime are unchanged from v0.1.0. The latest model repair failed its improvement test. The new real-patch exact-execution tool is a baseline, **not a trained model**. None of the four controller candidates is promoted as an accepted model.
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  ## The experiment
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  A controller records progress and retries failed operations. An edit to its recovery logic can delay completion or repeat work. The research question is whether pre-action evidence can predict that consequence.
 
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  > Controller weights and runtime are unchanged from v0.1.0. The latest model repair failed its improvement test. The new real-patch exact-execution tool is a baseline, **not a trained model**. None of the four controller candidates is promoted as an accepted model.
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+ ## The goal
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+ Laxmi's long-term ambition is a **testable software world model**: a system that maintains a predictive view of software state as evidence arrives. Given the current state, execution history, a proposed action or code change, and declared operating conditions, it should forecast possible consequences **before execution**, express uncertainty, and revise its view when new observations arrive. A useful forecast would help an engineer decide what to inspect, test, change or leave alone.
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+ The research path has three stages:
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+ 1. **Predictive state:** learn action- and source-conditioned outcomes, including bounded multi-step effects and differences between proposed changes. Measure forecasts against actual outcomes and strong methods given the same information.
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+ 2. **Prospective advice:** save forecasts before real controller actions, then test whether the advice improves a human review decision at acceptable error, coverage, latency and cost.
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+ 3. **Broader engineering assessment:** use source and pull-request context, observed history and explicit constraints to assess likely consequences, compare a finite set of alternatives, and explain findings with traceable evidence.
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+ The ultimate aspiration is useful engineer-like work within a **defined role and measurable constraints**. Progress is measured by prospective outcomes and decisions, including honest abstention when evidence is insufficient. This v0.1.1 release is an early, bounded controller experiment toward the first stage. It has not established a general software world model, a qualified advisory, or autonomous engineering capability.
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  ## The experiment
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  A controller records progress and retries failed operations. An edit to its recovery logic can delay completion or repeat work. The research question is whether pre-action evidence can predict that consequence.
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@@ -4,7 +4,7 @@ f42243d8ec7031d491961ebcbe70b70c9d410b1964f2080c73c4ab03bc9b01d8 CITATION.cff
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  cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30 LICENSE
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  3a66b62901c108c4f8946247ff7a773f73ac3bcec0b8a34286eb921164e97d5f LICENSE_SCOPE.md
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  3baa95979dcbe90444a854d04bbb6546c799e2077d9a69cfa34014a5c6512950 NOTICE
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- af5cdcd4819c7997c61a1f19f1dbff5a4b254547ae6395f88964e0b0e6d5c24a README.md
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  f7dbdd9349019149fc54ae8bcf3edf442d5b53a62bf0905b57b88a1e3379a48c RELEASE_SCOPE.md
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  225a71bb67d619e70f1aec0313d2c5791d0a94ac3942297ad12ba284269cddd8 candidates/17-normalized/consumer.json
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  05478c5c7bf33bce2df7f7b1ffdffaa11dab3d6220558b1c2bb4d8432a5230e7 candidates/17-normalized/inference/config.json
 
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  cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30 LICENSE
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  3a66b62901c108c4f8946247ff7a773f73ac3bcec0b8a34286eb921164e97d5f LICENSE_SCOPE.md
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  3baa95979dcbe90444a854d04bbb6546c799e2077d9a69cfa34014a5c6512950 NOTICE
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+ c3ad6a03353f031329bd920ef3fea1db63c1e2f2ac2b99c7ea95fc93c112bf0e README.md
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  f7dbdd9349019149fc54ae8bcf3edf442d5b53a62bf0905b57b88a1e3379a48c RELEASE_SCOPE.md
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  225a71bb67d619e70f1aec0313d2c5791d0a94ac3942297ad12ba284269cddd8 candidates/17-normalized/consumer.json
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  05478c5c7bf33bce2df7f7b1ffdffaa11dab3d6220558b1c2bb4d8432a5230e7 candidates/17-normalized/inference/config.json