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Maritime nuclear energy startup Bluecore Energy has raised $10 million in a pre-seed funding round led by Slauson & Co.

More than one-eighth of apps analyzed contained foreign code.

Tesla has revealed its upcoming Cybercab design with a built-in SpaceX Starlink V5 dish.

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It starts at just under $25,000, but the hybrid won't arrive until next year.

I first slipped on Halliday's original smart glasses at CES 2025. I was not a fan. The glasses had a tiny, movable display window embedded into the frame that was incredibly finicky to see, and my 30-minute demo left me with achy eyeballs. It was an interesting concept with terrible execution, especially compared to the […]

Nintendo does a lot of weird things, but Splatoon might just be one of the strangest - or at least the boldest. The series started as an attempt to muscle into the ultra-competitive online shooter space, but in a way that feels a world away from the violence and bombast of Call of Duty or […]

New gaming gear is always promising to shave milliseconds off latency or response time. The improvements usually aren't obvious. But the Glorious GHS InfinitePlay wireless headset, on the other hand, could save you far more than just milliseconds: It has the fastest hot-swap battery system I've ever used, and the headset doesn't die when you […]

Halliday’s G2 glasses can listen to and summarize your workplace meetings—with no video involved.

It is time to bring opposites together, to stir up these stagnant waters, and to restore an industry that is dynamic from within, with multiple connections that were previously impossible or unimaginable. In the previous parts of this series, we explored how PureScript acts as a quiet rewrite of the Web , offering a territory of mathematical precision above JavaScript, and how its universal polymorphism allows it to target wildly different runtimes like Node.js, Erlang's BEAM, Chez Scheme, etc. But hey, what about the elephant in the room? Yes, what is running the majority of the web, today, in the shadow? You know. The eternal one, the big one, the one whose death everyone talks about, but who never truly dies. PHP. While the modern JavaScript ecosystem (among others) races toward edge computing and containerized microservices, around 70% of the web is still powered by PHP . From legacy WordPress sites to affordable shared hosting (cPanel, OVH, GoDaddy, basic LAMP stacks), a massive portion of the internet lives in environments where escaping the PHP runtime is either financially unviable, technically impossible, or simply unnecessary. And yet... For a long time, the PHP ecosystem has been left without a true, strictly typed functional and safe alternative, like TypeScript for Javascript. Even though recent PHP versions introduced fantastic features (short closures, match expressions, Fibers), the frustration that comes with its historical limitations and dynamic typing remains very real for some of its users. Very well! This is why I built phpurs : a brand new compiler backend that transpiles PureScript directly to modern PHP 8.4+ syntax. It is no longer a proof of concept. It is passing the official PureScript test suite , and it is ready for production. Here is how we bring the elegance of purely functional programming to the big web, while keeping deployment as simple as a legacy FTP upload, or anything alike. The easy deployment paradox In modern DevOps, deplo

Building AI Agents That Don't Hallucinate: Structured Workflows, Guardrails, and Per-Step Evaluation How we replaced fragile prompt chains with typed schemas, validation gates, and evaluation at every step — 94% task success vs 60% baseline The Prompt Chain Trap January 2024. We built a "research agent" — 12 prompts chained together: Decompose question → 2. Search planning → 3. Execute searches → 4. Extract facts → 5. Synthesize → 6. Fact-check → 7. Format → ... It worked 60% of the time. The other 40%: Step 3 returned malformed JSON → Step 4 crashed Step 5 hallucinated citations → Step 6 missed it Step 7 output wrong format → Downstream consumer failed No visibility into which step failed Debugging meant reading 12 LLM calls' worth of logs. Adding a step broke three others. The Shift: Agents as Typed Workflows We moved from prompt chains to structured workflows with: Pydantic schemas for every step input/output Guardrails that validate and auto-retry Explicit state machine (not implicit chaining) Evaluation harness per step (not just end-to-end) ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ Decompose │──▶│ Search │──▶│ Extract │──▶│ Synthesize │ │ Question │ │ Planning │ │ Facts │ │ Answer │ │ │ │ │ │ │ │ │ │ In: Query │ │ In: Plan │ │ In: Results │ │ In: Facts │ │ Out: SubQ[] │ │ Out: Steps │ │ Out: Fact[] │ │ Out: Answer │ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ │ │ │ │ ▼ ▼ ▼ ▼ [Schema] [Schema] [Schema] [Schema] [Guardrail] [Guardrail] [Guardrail] [Guardrail] [Eval: 0.9] [Eval: 0.85] [Eval: 0.9] [Eval: 0.95] Core Abstractions # agent_eval/schemas.py from pydantic import BaseModel , Field from typing import Literal , Any class DecomposeInput ( BaseModel ): user_query : str context : dict = Field ( default_factory = dict ) class DecomposeOutput ( BaseModel ): sub_questions : list [ str ] = Field ( min_length = 1 , max_length = 5 ) requires_tools : bool reasoning : str class PlanInput ( BaseModel ): sub_questions : list [