Open by design
Make the signals, assumptions, and decision paths inspectable.
The agentic economy needs a trust and incentive layer.
Rishabh Banga builds AI workflows, trust systems, and structured-community infrastructure that make agentic participation more trusted, incentive-aware, and governable.
LIVE SYSTEM MAP01 / 05
01Activitypeople + agents
02Signalsreputation + context
03Trust layerevaluate + explain
04Actionreward + escalate
HUMAN
OVERSIGHT
OVERSIGHT
Autonomy alone creates noise. Trust makes participation valuable.
Humans and agents will coordinate, recommend, transact, and respond to incentives. The winning product layer is not the agent itself. It is the infrastructure around agentic participation.
Trust is a product feature
Evaluation, explanation, escalation, and accountability belong in the workflow.
Incentives shape behavior
Reward trusted participation and make reputation useful across the system.
From community activity to an operating layer.
A product sprint across AI workflows, trust systems, and structured-community GTM. Each artifact strengthens the next.
Artifact 01Functional workflow
WeKamp Digest
From community activity to operator guidance.
Activity→Signals→Guidance
A functional AI workflow translating member, post, event, comment, visit, and engagement activity into trust and engagement signals operators can act on.
Key product moveTrust became an operating surface, not a passive dashboard.
Artifact 02Platform thesis
Trust decision layer
Trust as shared infrastructure for humans and agents.
Show relevant contentReward trusted behaviorEscalate high-risk casesExplain each decisionBlock harmful actions
Agents need permissions, reputation, incentives, dispute paths, and legible decision histories before they can participate economically.
Artifact 03GTM wedge
Structured communities
The beachhead for the agentic economy.
Recurring cadenceClear operatorsTrust-sensitive interactionReal coordination overhead
Where coordination is hard, workflow design creates defensible and sticky product value.
Activity→Signal translation→Workflow→Trust + incentive layer→Action→GTM
Products that make trust visible.
Each system turns ambiguous AI participation into evaluation, signals, and accountable action.
01 / TRUST INFRASTRUCTURE
Network Guardian
Pre-connection Wi-Fi trust that turns diagnostics, reputation history, and confidence signals into a decision before the first packet leaves the device.
30 daysfirst version shipped
View product concept ↗02 / COMMUNITY TRUST
Kampd
AI-powered trust, discovery, ranking, and moderation systems with policy-driven review paths.
25% activation lift40% less manual review
03 / RELIABLE AI
TravelTech
A connected planning, booking, and concierge workflow designed around constraints and valid outputs.
98%+ valid itineraries12s P95 pipeline
04 / PRODUCT INFRASTRUCTURE
iPRD
A deterministic product-specification workflow that converts rough product thinking into structured, inspectable, executable specifications.
“Make the decision path visible before the system ships.”
Ideas for the people building what comes next.
Talks and trainings across open-source AI, runtime trust signals, reliable agentic systems, and responsible adoption.
Open-source AI / All Things Open 2026
AI Systems Fail Silently
Building trust layers with open source for reliable AI.
Event profile ↗
Open-source AI / FOSSY 2026
From Prompts to Runtime Signals
Making open-source AI systems easier to evaluate, monitor, and trust.
Schedule ↗
Trustworthy AI / IEEE WF-PST 2026
Trustworthy Agentic AI
Evaluation gates, escalation paths, and human review for public safety workflows.
Real-world AI / ICML 2026
Beyond the Model
Building AI systems that work in the real world.
Founder training / YSpace
Hiring Your First AI Employee
Delegating real work to agents without losing judgment or control.
Product leadership / TPMA
Practice PMing Multiple Products
Focus, prioritization, and decision-making across several products.
Teaching / Stanford University
Code in Place
Section lead for Stanford's intro Python course, supporting live problem-solving and debugging.
Invite Rishabh to speak, facilitate a workshop, or advise your team on trustworthy AI.
Invite RishabhA few beliefs I keep testing.
Short notes, diagrams, and product questions from the work.
Trust is not a badge. It is a system behavior.
Users trust products when decisions are legible, recoverable, and accountable.
Every agent needs a reason to behave well.
Reputation and reward systems are product mechanics, not just economic theory.
The best AI product move may be a new operating surface.
Turn messy activity into guidance people can use, inspect, and improve.
Product judgment for systems that need to work in public.
Rishabh Banga is an AI product leader and operator working across enterprise agents, trust systems, workflow infrastructure, and structured-community GTM.
His work connects product strategy to the details that make participation safe and useful: evaluation, incentives, human oversight, escalation, and adoption.