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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
Stateflow Labs | ALGOgent Runtime & Adaptive Runtime for ...
stateflow-dev · 2026-06-05 · via Hacker News - Newest: "AI"
Open Source · MIT License · Python 3.10+

Build Python Systems
That Survive Failures

Two open-source SDKs built around one belief — the biggest AI problems in production are not model problems. They are runtime problems.

"Runtime systems don't justify unreliable agents.
They acknowledge that failures are inevitable
and handle them in a controlled, recoverable way."

No GPU Required No External Services No Cloud Lock-in Pure Python MIT License

Built in public.  ·  Real experiments.  ·  Real failures.  ·  Real recovery.  ·  Open source under MIT.

// open source sdks

Two SDKs. One mission.

Two approaches to the same problem: building Python systems that survive failures.

Entry Level · Start Here

ALGOgent Runtime

Lightweight Runtime Intelligence SDK

A self-contained SDK for building resilient automation scripts and AI pipelines. Synchronous, plug-and-play, zero configuration. Drop it into any Python project and get retry logic, state persistence, checkpoint recovery, and confidence scoring without any external services or async overhead.

Runtime Engine Retry + Backoff State Persistence Checkpoint Recovery Confidence Scoring Event Bus Structured Logging Runtime Metrics

Python 3.10+ Synchronous JSON State MIT

Advanced · Advanced Runtime Layer

Adaptive Runtime

Runtime Intelligence Layer for Stateful AI Systems

A full async runtime intelligence layer built for production AI systems that need to survive real conditions. Five core engines work together to analyze context, score confidence, make decisions, persist state to SQLite, and recover from crashes automatically — without GPU, without cloud, without heavy ML frameworks.

Context Engine Confidence Engine Decision Engine State Engine Recovery Engine Async Event Bus SQLite Persistence Runtime Metrics

Python 3.11+ Full Async SQLite State MIT

// side by side

Which one is right for you?

Feature ALGOgent Runtime Adaptive Runtime ★
Target use caseAutomation, simple AI pipelinesLong-running AI systems and automation workloads
Execution modelSynchronousFull async (asyncio)
State persistenceJSON fileSQLite (async)
Checkpoint recovery Built-in Built-in
Confidence scoring Basic Adaptive (decay + history)
Context engine Risk + stability analysis
Decision engine Rule-based action selection
Event bus Sync pub/sub Async pub/sub
Structured logging Color-coded
Setup complexityZero configMinimal (pydantic, aiosqlite)
GPU required Never Never
Runs on $5 VPS Designed for it
LicenseMITMIT

// real world experiments

Proof Through Execution

These SDKs are not theoretical concepts.
The following examples were executed using real Python code and runtime scenarios.

algogent — sender.py

$ python -m algogent.examples.sender

SUCCESS

Message Email sent successfully

Status SUCCESS

Provider Gmail SMTP

Execution Completed

ALGOgent Runtime

Existing Automation Script

A third-party Gmail automation script was executed through ALGOgent Runtime without modification.

  • Existing code reused
  • Email delivery successful
  • Pure Python execution
  • No cloud dependency
  • No infrastructure required

algogent — sender.py

$ python -m algogent.examples.sender

FAILED

Message Error sending email

Code 535

Reason Authentication Failed

Status FAILED

Error BadCredentials

ALGOgent Runtime

Failure Detection

The same automation workflow was executed after removing Gmail credentials.

  • Authentication failure detected
  • Error surfaced safely
  • Runtime remained stable
  • Failure path verified

adaptive — decision_engine.py

$ python -m adaptive.examples.runtime

SIMULATION

service_overload throttle_requests

anomaly_detected flag_for_review

timeout cache_warmup

degraded_service health_check

recovery_needed run_recovery

Adaptive Runtime

Runtime Decision Flow

Multiple runtime events were injected into the system to observe contextual decision making.

  • Context analyzed
  • Confidence calculated
  • Action selected
  • State persisted
  • Recovery workflow triggered

// open development

Built in Public

Stateflow Labs is developed openly on GitHub.
Every feature, experiment, and iteration is visible to the community.

// runtime philosophy

"Most AI problems in production
are not model problems.
They are runtime problems."

Both SDKs are built around the belief that future AI systems need memory that survives crashes, resilience with checkpoints and retry logic, contextual behavior that adapts to real conditions, and confidence awareness — knowing how certain a decision is.

Not just prompts. Not just workflows. Runtime intelligence.