Whitepapers
A framework to work with. Frameworks for the questions behind agentic AI. Explore working papers on release evidence, authority and the decisions your team needs to make.
10 working papers · Explore the collection
A release decision has a shelf life. Identify which changes invalidate its assumptions, choose proportionate checks, and connect production signals to decisions about continuing, constraining, correcting or withdrawing an agent workflow.
Compare agentic work with simpler alternatives, expose the dependencies behind a promising demonstration, and fund a bounded experiment with a clear decision at its end.
Turn agent permissions into an enforceable action contract. Separate a model's suggestion from a resource owner's authorisation, test the boundary, and make delegation and revocation reviewable.
Define the contracts around an agent's decisions: what state it trusts, which actions can execute, how interrupted work resumes, and what evidence an operator needs to recover safely.
Replace a single pass rate with a reviewable chain of requirements, cases, observations and judgements. Distinguish task quality, control failures and uncertainty before increasing an agent's exposure.
Governance becomes useful when it changes a decision. Connect each agent workflow to an accountable owner, explicit operating conditions, proportionate evidence and a practical route for exceptions and withdrawal.
Connect agent activity to accepted business outcomes, establish a credible comparison, and distinguish useful capacity from realized financial value before deciding whether to scale.
An agent's information footprint extends beyond the conversation. Map the copies, derived records and retrieval paths that influence future actions, then connect each to purpose, access, retention and verifiable handling.
A working paper for leaders who need to explain why an agent workflow is ready for its next release. Includes a proposed evidence-pack structure, decision table and review agenda.
A working paper for the moment an AI system moves from advice to action. Map identity, permissions, approvals and recovery into an authority model your team can review and test.
Bring one agent workflow and the decision in front of you. Gaurav Tiwari replies personally within 1 working day.
A little more clarity
Start with the questions that shape a better decision.
Each paper turns a recurring agentic AI decision into a reusable working structure, such as an evidence-pack model, authority register, review agenda or boundary-test plan.
The current papers are versioned conceptual frameworks informed by cited sources. They do not claim empirical validation, client outcomes or universal completeness.
Use the questions and tables to prepare a product, engineering, security or governance review. Applying the framework to a live system requires system-specific evidence and appropriately qualified review.