Ask HN: Anyone still coding like 2021? Where do you work?
Hacker News users debate coding without LLMs, with one developer fired for refusing AI tools and others describing daily hand-coding practice to counter skill atrophy.
An Ask HN thread collects experiences of developers who still write code without LLM assistance. One contributor says he was fired for political reasons after refusing to use LLMs despite adequate stated performance, and observes fewer job ads now require LLM use. Others describe starting each day with a LeetCode problem or 30-60 minutes of hand-coding to stay sharp, contractual bans on AI-generated code for a government-adjacent embedded product over unresolved copyright issues, and inconsistent corporate policies where ChatGPT or Codex use flip-flops between allowed and blocked while a CIO mandates 70-80% AI-generated code next year.
CISOs Race to Control AI Agents Without Destroying Their Value
Team8 survey: 78% of CISOs name AI and agent security their biggest pain point as over-privileged agents expand attack surface.
Team8's annual CISO Village survey reports that 78% of security leaders cite AI and agent security as their biggest pain point, twice the second-ranked concern (39%), while 71% are experimenting with or augmenting security tools using AI agents. Team8 CISO Tim Brown warns that employee-built agents created with tools like Claude Code, Cursor and Codex can take unintended harmful actions, such as poking around production systems, because prompt imprecision combines with non-deterministic model behavior. Brown recommends building guardrails into the agent development process to limit where agents can go and what they can do, without destroying business utility. He also urges greater transparency and experience sharing among security leaders facing the same agent security problems.
7th September – Threat Intelligence Report
Check Point weekly bulletin: exploited SonicWall SMA 1000 zero-days (CVE-2026-83548/49), JFrog Artifactory auth bypass, and a 2.8M-patient Baylor Genetics breach.
Check Point's weekly bulletin covers breaches including Thomson Reuters' C-Track platform (court records across 11 US states and Canada), Baylor Genetics (2.8M patients and employees, SSNs included), Hit casinos in Slovenia, and Dropbox (~5,000 accounts via abused Lenovo email verification). SonicWall patched two exploited SMA 1000 zero-days, including CVE-2026-83548, a CVSS 10.0 pre-authentication SSRF, while JFrog fixed exploited authentication bypass CVE-2026-82329 (CVSS 9.8). Malware and actor coverage includes Gambling Goblin, JSCeal, Mirage Kitten's NodeRabbit/PollCat campaign, and DPRK Contagious Interview macOS activity, plus a FalconFlank privilege-escalation PoC against CrowdStrike Falcon.
DataGrout helps enterprises control AI usage, governance and LLM costs
SelectHub launched DataGrout, an LLM cost and governance platform combining dynamic context pruning, symbolic inference and MCP gating, claiming about 60% token reduction.
SelectHub launched DataGrout, an LLM inference optimization and AI governance platform combining dynamic context pruning, a symbolic inference layer, and an MCP gateway with per-call token and cost monitoring. Early tests claim roughly 60% token reduction on data-intensive ERP and CRM integration tasks without accuracy loss. The platform connects via its Conduit SDK, MCP or JSON-RPC, offers its own MCP servers for SaaS apps such as Salesforce, SAP and ServiceNow, and supports bring-your-own-key LLM access or gateways like Amazon Bedrock and Kong.
τ^τ-Bench: An Environment for End-To-End, Realistic Agent Construction
New τ^τ-bench tasks coding agents with building deployable customer-service agents; best config, Claude Opus 5, passes only 23.9% of simulations.
Researchers introduce τ^τ-bench, an end-to-end benchmark where a developer agent must build a complete customer-service agent from real business records, a client with requirements, a production API, an inherited codebase, and cost/model limits, then is scored by deploying it against held-out simulated users. Across 53 tasks in four domains, the strongest configuration, Claude Opus 5 under Claude Code, passes just 23.9% of evaluation simulations versus an 82.2% expert-authored reference ceiling. Failure modes mirror those of human developers: shallow queries instead of deep record comprehension, almost no client communication, and shipping the first architecture that runs rather than experimenting.