Hieu Luong | HimiTek

A one-person AI studio needs policy as code: budget caps, data boundaries, release gates, and an audit trail for agent actions. The founder approves exceptions; automation handles routine work. #AI #Solopreneur

MCP servers are production API surfaces. Version tool schemas, pin server releases, validate inputs at the gateway, log every call, and canary new tools against replayed workflows. A changed description can alter agent behavior. #MCP #AI

Agents should present proofs, not profiles: a Verifiable Credential can confirm “licensed for this action class” without exposing identity. Add selective disclosure and revocation checks, or agent-to-agent trust becomes unverifiable roleplay. #DID #AI

Audits find bugs; formal verification checks stated invariants. Specify solvency and authorization properties, model-check them, then fuzz paths the proof excludes. Block deployment until each finding has a regression test. #SmartContracts #Security

Autonomous agents need delegation-aware credentials: bind each capability to an audience, expiry, nonce, and maximum delegation depth. Without depth limits, valid authority can recursively spread across an agent swarm. #DecentralizedIdentity #AI

MCP turns business actions into callable interfaces. In production, every tool needs an idempotency key, bounded timeout, and compensating action—otherwise retries can duplicate refunds, shipments, or payroll runs. #MCP #AI

Enterprise AI agents should receive secrets only after TEE remote attestation verifies the approved code hash and policy. Record the attestation, task receipt, and output hash onchain; release keys per job, never per agent. #ConfidentialCompute #Web3

A one-person AI studio needs governance that survives the founder’s absence: give every agent a budget, owner, expiry, and kill switch. Centralize logs, automate policy checks, and review exceptions weekly. #AI #SoloFounder

MCP production failures often start with schema drift: pin tool versions, publish JSON Schema, and contract-test every server against real workflow fixtures. A changed enum can silently route an agent to the wrong business action. #MCP #AIOps

A DID proves control of a key. It says nothing about an agent’s runtime or authority. Issue VCs for code hash, policy version, sponsor, and spend ceiling; require them at every handoff. #DID #VerifiableCredentials

Autonomous agents need verifiable credentials with machine-checkable delegation: issuer, scope, expiry, and revocation status. Bind each credential to a DID key; verify audience and nonce before execution. #DID #VerifiableCredentials

MCP in production needs context provenance: tag resources with tenant, source, timestamp, and auth scope. Reject stale or cross-tenant context before tool calls. Trace the decision and request. #MCP #AIOps

MCP tools need transactional semantics before agents touch business systems: declare idempotency keys, dry-run behavior, side effects, and rollback limits in the tool contract. Retries turn vague APIs into duplicate invoices. #MCP #AIOps

Autonomous workers on a Linux VPS need a kernel boundary and a stop button: run each job as a systemd unit with private mounts, dropped capabilities, seccomp, egress limits, and human approval for shell, secrets, and production writes. #Linux #AIOps

Audits miss invariants they never state. Specify balance conservation, access control, and replay safety; prove them with SMT/model checking. Fuzz the gaps, then review proof assumptions before deployment. #Solidity #FormalVerification

LLM cost drops with quality-aware routing: send easy requests to small models, reserve frontier calls for low-confidence or high-risk cases, and fall back on timeout, schema failure, or quality regression. Track cost per accepted answer. #LLMOps

A DPP for export needs claim-level evidence, not a polished ESG score: material origin, calculation method, reporting period, and expiry for each field. Buyers can reject one stale claim without invalidating the product. #DPP #ESG

MCP production systems need tenant-aware context and tools. Tag every retrieved fact with owner, freshness, and authorization scope; reject cross-tenant context before a model turns it into an action. #MCP #AI

MCP automation fails when retries duplicate side effects. Require idempotency keys, dry-run support, and compensating actions for every mutating tool; a timeout must never trigger a second payment, ticket, or deployment. #MCP #AIOps

Export DPPs need versioned schemas, signed transformations, and an audit trail for every custody handoff. Without them, ESG data becomes unprovable when suppliers change systems or customs requests lineage. #DPP #ESG