LAPS Enterprise Framework
Learn. Act. Prove. Sharpen.
A practical framework for building with AI, building AI systems, and serving people who use AI.
The operating loop
A lap is a focused cycle of work that closes with evidence and a decision. The next lap starts with what you learned.
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Understand the objective and relevant evidence.
Agree the objective, relevant evidence and the uncertainty that matters next. Set expectations, a decision owner, and limits on time, cost and authority before work begins.
Help a service adviser find the right policy clause. Check existing retrieval failures, agree representative test cases, and keep customer messaging outside the mandate.
Leave with: a shared objective, a learning question and agreed expectations.
A lap can end in accept, revise, stop or blocked. Unfinished evidence stays visible.
A shorter path to useful feedback
Explore possible feedback intervals across ten working days. Choose a rhythm to see what it asks of the team.
Daily laps
Bring ready work, clear acceptance evidence and reserved review capacity. Close the day with an accountable decision and refreshed shared knowledge.
Illustrative cadence, not a productivity promise. Scrum can already include feedback throughout a Sprint. A lap’s clock, release approval and observation of business outcomes are separate.
Scope the AI you actually use
Select the ways AI appears in your initiative. More than one can apply; each adds responsibilities to the same lifecycle.
The manifesto
Six values guide the work when speed, certainty and responsibility compete.
Measure a useful result that works within agreed limits.
Expose uncertainty and make commitments proportionate to what is known.
Learn before increasing cost, exposure or autonomy.
Bring the necessary skills to the outcome and preserve their judgment.
People own decisions. AI works within enforceable mandates.
Keep checking behaviour, value and recovery after release.
The complete lifecycle
Ten decision stages, revisited as evidence changes. Small laps can run within and across stages; these are not ten separate departments.
Set the conditions for responsible work.
Understand the problem and baseline.
Agree behaviour and acceptance.
Make boundaries and recovery explicit.
Make data and evaluation ready.
Perform bounded, traceable work.
Test the system and challenge the evidence.
Increase exposure deliberately.
Observe behaviour, cost and real value.
Improve deliberately. Close responsibly.
Two ways to begin
The same principles, adapted to your context. Small team size does not reduce the consequences of a critical use case.
Coordinate delivery, product, data, security, risk and operations around shared outcomes.
Use a compact set of records and combine roles where competence and independence allow.
The living paper
A complete operating framework, with practical examples, original diagrams and reusable templates.
GAURAV RAJWANSHI
LAPSBy Gaurav Rajwanshi. Informed by work with high-profile enterprise clients over the last two to three years, published professional reflections and practitioner discussions.
Client identities and confidential details are excluded. This is a proposed framework under review; it does not claim client endorsement or independently proven performance gains.
Free to use and adapt with attribution to the author and version. Third-party sources retain their own terms.
Standards inform the controls. Your context determines their application. These organisations do not endorse LAPS.
PACE contributes selected workflow, context and review patterns. LAPS retains its own enterprise accountabilities, evaluation requirements and controls for AI products and delegated user actions.
Take the paper with you
Get the complete v0.8 PDF. Tell me a little about your context and the challenge you are working on.
The complete framework is also available to read online without registration.
Shape the next version
Challenge a claim, suggest an improvement or share what happened when you tried a lap. Please keep client and personal information out of examples.
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Public beta · v0.8
LAPS is the working name. Future changes will be published with a dated version record, while this edition remains available.
0.8 · 14 October 2026
Adopts the author’s expansion: Learn, Act, Prove, Sharpen. Aligns the interactive cycle, paper and diagrams with those four actions, retaining evidence, accountability and release controls.
0.7 · 14 October 2026
First public beta: three AI overlays, manifesto, full lifecycle, daily and half-day laps, enterprise and lighter routes, practical templates and source notes.
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