DE

Founding partner at @EosTalent . Leading GTM recruitment for early stage AI start ups 🤖

[Eos Talent @EosTalent]

hiring for a networking engineer at a Solana firm that has been in the trenches for years.

you will work on critical infrastructure: validators, RPC servers, networking systems in Rust. systems-level optimisations, monitoring, resilience at scale.

needed:
-> 3+ years systems engineering or infrastructure, proficient in Rust for high-performance applications
-> strong distributed systems background and benchmarking experience
-> deep understanding of network protocols: TCP/IP, UDP, QUIC
-> familiar with monitoring stacks: Prometheus, Grafana, OpenTelemetry

HPC experience a strong bonus. small, highly technical team. US only - open to remote but priority for NYC candidates

DM @EosTalent for a warm intro.

[Anthropic @AnthropicAI]

Claude Fable 5 will be available again globally tomorrow.

After a series of productive conversations with the US government, we're redeploying the model with a new set of classifiers to target and block more cybersecurity tasks. In the near term, some routine tasks like coding and debugging will fall back to Opus 4.8. We’ll continue to refine these classifiers over the coming weeks to reduce false positives and better distinguish genuine misuse from legitimate requests.

We’ve also begun drafting a consensus framework—with Amazon, Microsoft, Google, and other Glasswing partners—for assessing the severity of AI jailbreaks and how AI developers should respond to them. We invite other industry partners and model providers to join us in this effort.

Finally, we’re scaling up our collaboration with the US government on model testing and safeguards. This will include pre-release access to models and safeguards for evaluation, information sharing on jailbreaks and misuse, and dedicated resources for joint research.

Thank you to our users for your patience, and to our partners across the government, industry, and the research community who worked alongside us to make Fable 5 available again.

Read our full blog: https://t.co/VHyum831ri

[a16z @a16z]

AI native startups have fewer employees

Charts of the Week: https://t.co/qmjdkZzisp

[Wisedocs @Wisedocsai]

Today at 2 PM ET, join @jennaearnshaw and @_diginsurance for a live Wisedocs webinar on pressure-testing claims with AI across demands, bills, and medical records.

Register here
https://t.co/2S1MGEU9kj

[Brian Armstrong @brian_armstrong]

How to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts. With better defaults, routing, and caching.

Better Defaults (not Usage Caps) – Engineers can choose any model they want, but defaults matter. We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task. 91% of our employees were never hitting their usage caps, so instead of lowering caps and driving up alerts, we're moving to cheaper defaults. Note that code reviews use a diversity of models, so they can check each other's work.

Better Routing – In our custom harnesses, we preprocess prompts and route to the best model for the job, considering cache hits and model pricing. For instance, you may want a frontier model for planning, but not for execution where they can be overkill. Ultimately, humans shouldn't be choosing models - AI can automate this task.

Better Caching – Cache misses are the easiest way to drive your cost up. All of our requests are cache aware, so we’re reusing a warm cache wherever possible. For example, our cache hit rate went from 5% → 60% in LibreChat once properly implemented.

Keep Context Lean – Start fresh sessions when switching tasks. Scope file context narrowly. Disconnect unused tools. Don't just compact. The goal isn't fewer tokens used, it's fewer tokens wasted.

Better Visibility – Our engineers can use as many tokens as they want, from whatever model they want, but we’ve made usage visible – and the more you spend on AI, the more impact we expect.

The goal isn't to suppress usage. It's to build the infrastructure that makes exponential growth sustainable.

Putting this into practice has cut our AI spend nearly in half, while our token usage continues to grow.

[Anthropic @AnthropicAI]

Since June 12, we’ve been working closely with the US government to restore access to Claude Mythos 5 and Fable 5. Today, the government notified us that Mythos 5, our strongest cybersecurity model, can be redeployed to a set of US organizations that operate and defend critical infrastructure.

We’re restoring access for these organizations quickly, and we’re continuing to work with the government to expand access to Mythos 5 and make Fable 5 available for general use again.

[OpenAI @OpenAI]

Introducing a limited preview of GPT-5.6 Sol, our next generation frontier model, as well as GPT-5.6 Terra, a balanced model for efficient, everyday work, and GPT-5.6 Luna, a fast and affordable model for high-volume work.

https://t.co/OoM83SyISN

[Itamar Golan 🤓 @ItakGol]

If you come from the future you can apply

[Paul Graham @paulg]

The best predictor of success for tech companies, at every stage from during the YC batch to public company with billions in revenue, is the rate of shipping new stuff.

[Luke Sophinos @lukesophinos]

A lot of vertical SaaS founders underinvest in GTM data. Bad data kills great products and great reps.

The best vertical SaaS companies treat data as a competitive advantage. They maintain 80-90% of their TAM in their CRM, enriched with vertical specific attributes (size, tech stack, segment), and run deep filters to prioritize accounts.

When your entire TAM is mapped, you can be strategic about territory planning, rep hiring, and messaging. You're not guessing.

How to build it: licenses/permits, Google Maps scraping, vertical databases, tools like Orbital. Then enrich with ICP signals. Then score into 3-5 tiers from "drop everything" to "don't touch for 24 months."

Tailor outreach by segment. Companies using a competitor need different messaging than pen-and-paper shops.

Historically, vertical SaaS winners built this in house with engineers and data teams. Now platforms exist. But most founders still realize too late that data quality is distribution.

[Austin Hughes @austinh___]

We built Claude for outbound sellers.

AEs & SDRs can harness GTM engineering through chat across 40+ data sources, no technical skills required.

We’ve had 57,548 queries in our first few weeks of beta, growing 45% w/w.

The teams winning outbound in 2026 are already on it. Self-serve now live here: https://t.co/pwdSGTG0Hq

[Damian Player @damianplayer]

Palantir invented the forward deployed engineer role in 2006.

embed an engineer inside the customer. ship production code in their environment. own the technical outcome.

Alex Karp on the idea: “forward deployed engineers are stolen from french restaurants.”

20 years later every AI company is copying it. OpenAI, Anthropic, Ramp, and Salesforce all hiring them.

job postings up 800% this year.

[DE @EarnshawDan]

@RainSoldier @MOT_Matt

[DE @EarnshawDan]

@ellis_platten Shouldn't expect to take a club sponsored by an energy drink seriously either

[DE @EarnshawDan]

@LufcZovic How can you criticise Harrison for inconsistency and then mention Gnonto in the same breath? Lmao

[DE @EarnshawDan]

@KenzoBrown23 @PhilHay_ No, it should be on people to not act like fucking psychos. What do you expect Big Sam to do to stop people turning up at Bamfords house ffs.

[DE @EarnshawDan]

@PhilHay_ What's the point of a loan deal?

[DE @EarnshawDan]

@DanRegan_Comedy Interested.

[DE @EarnshawDan]

@Joey7Barton Not sure why anyone is expecting any respect for women from a man who was physically violent to his partner.