Hieu Luong | HimiTek

LLM cost drops when routing follows failure modes: cheap models handle drafts, strong models handle ambiguity, and fallbacks trigger on schema or grounding failures—not vague “low confidence.” Log quality by route, then tune thresholds against spend #HimiTek

TEE confidentiality fails when keys arrive before attestation. Gate decryption and tool credentials on measured agent code, policy hash, and platform state. Sign every decision for audit. #AI #Security

DPP compliance breaks at the exporter’s weakest supplier: map each material claim to a batch ID, evidence source, timestamp, and verifier before customs asks. A PDF sustainability report won’t survive a product-level data check. #ESG #DPP

AI workers belong in disposable systemd units: private /tmp, read-only root, dropped caps, seccomp, and egress allowlists. Human approval gates package installs, writes, and shell escalation. #Linux #AI

Audit habits catch blind spots proofs miss: write exploit narratives, encode invariants, fuzz state transitions, and review every external call. Prove critical paths, then run those properties against a production fork before release. #SmartContracts #DeFi

Autonomous agents need DIDs for continuity and verifiable credentials for authority. Before a high-impact API call, verify issuer, scope, expiry, and revocation status. A wallet address alone proves possession—not permission. #AI #Identity

Formal verification only covers the model you wrote. Compare specs against deployed bytecode, pin compiler versions, and make CI reject proof gaps. A verified contract with an incomplete threat model is still shippable risk. #SmartContracts #Security

A one-person AI studio needs a control plane: Git for code, Postgres for jobs, encrypted secrets, immutable run IDs, and weekly restore tests. If you can’t reconstruct last week’s output, you don’t govern it. #AI #Solopreneur

Autonomous workers should earn privilege per action: start jailed, propose a diff, then require a human-signed capability token before touching VPS state. Expire tokens and log the full decision chain. #AI #Linux

Export DPPs need change control: version product claims, hash supporting evidence, and reject shipments when the declared bill of materials diverges from the signed record. Customs clearance needs machine-verifiable traceability. #ESG #DPP

Audit habits that prevent exploits: define invariants, formally prove arithmetic and access-control properties, fuzz the gaps, then review every privileged call. Treat unverifiable assumptions as release blockers. #SmartContracts #Security

Govern a one-person AI studio with budgets, eval gates, and a kill switch: cap spend per workflow, route by task risk, replay failures before release, and pause any agent that exceeds its error or latency SLO. #AI #Solopreneur

Run autonomous workers as disposable Linux sandboxes: separate UID, read-only rootfs, capped CPU/RAM, seccomp, and deny-by-default egress. Gate shell, secrets, writes, and network changes through a human approval queue. #AI #Linux

Export DPP compliance breaks at the supplier boundary. Map every ESG field to an owner, source, timestamp, and jurisdiction rule; quarantine stale or unverifiable values before customs clearance. #ESG #DPP

Your one-person AI studio needs a control plane before more agents: version prompts and policy in Git, log every external action, and require approval for payments, deletion, and deploys. #AI #Solopreneur

For export supply chains, a DPP is only as defensible as its evidence trail. Bind material origin, repair history, emissions methodology, and responsible operator to signed event IDs; let customs verify a product snapshot, not a spreadsheet. #ESG #DPP

MCP tools need production contracts: version schemas, enforce idempotency keys, set timeouts, and return machine-readable errors. Without them, retries can turn one invoice, ticket, or refund into several. #AI #MCP

Treat agent identity as a cryptographic principal, not a username. Bind each verifiable credential to a key, require proof-of-possession for agent-to-agent requests, and record the delegation chain for audit. #AI #Web3

Cut LLM spend by routing on task risk, then make fallbacks measurable: cache deterministic work, cap retry depth, and run every model against the same eval set. A cheap route that fails silently costs more than a premium call. #AI #LLMOps

MCP becomes production-grade when tool results are treated as data, not truth. Bind each response to request ID, tenant, source version, and freshness window; reject stale or cross-tenant context before the model acts. #AI #MCP