Frank Wang

security @hellosurgeai. formerly headway, dbt labs, dell tech capital, mit, stanford.

[Frank Wang @ffwang2]

My newsletter, Frankly Speaking, is back! I'm launching a freemium version but with more consistent articles and hot takes on my experience as an engineer and former VC working in cybersecurity: https://t.co/g9dKH8DNwA

Subscribe here: https://t.co/ps7i0nTEIu

[echen @echen]

real instructions aren't lists of independent rules. they're entangled.

introducing ComplexConstraints — our new IF benchmark testing the kinds of IF constraints that show up in real work:

1. conditional constraints (fire only when specific conditions are met)
2. planning constraints (many reqs must be satisfied simultaneously)
3. multistep constraints (each step feeds the next)
4. implicit constraints (a competent colleague would just know)

models score from 0% to 40%

we also trained a 4B model on 1k examples -> it matched a model 60x its size, and the gains transferred to other IF benchmarks like MultiChallenge and AdvancedIF.

blog post: https://t.co/6yVrPgYnqq

leaderboard: https://t.co/98r464SdLv

[Frank Wang @ffwang2]

AI agents aren't just suggesting code anymore—they are autonomously running privileged actions in local terminal shells. This completely upends endpoint security.

All it takes is a single logic error for a local agent to pull down a malicious open-source package and run it on a developer’s laptop because it thought the dependency was legit.

In my latest newsletter, I look at the future of the endpoint market and where the real opportunities sit for incumbents and startups:

🔹 The Agent Architecture: Building endpoint software is brutal on battery and kernel stability. But just like @Cloudflare Warp or @zscaler did with SWGs, you can get away with a lightweight local agent if you route the heavy compliance and policy lifting to an elite global infrastructure.

🔹 The IT Operational Trap: Enterprise IT is stuck. Bloated companies have hyper-specialized teams doing manual tasks that AI will eliminate, making re-allocation highly political. The real market is lean startups where engineers moonlight as IT admins and need autonomous agents to patch and monitor fleet health out of the box.

🔹 The Platform Dark Horse: I’m cautiously optimistic about new plays like @Tanium Atlas. Complex, feature-heavy legacy platforms that are historically hard to use might actually benefit the most from AI. If you have 20 years of deep feature telemetry, you can use a natural-language interface to completely hide the plumbing and deliver immediate value.

The endpoint checkbook is going to split. AI-forward shops view budget as one big efficiency blob. Older enterprises are facing a massive political battle over the consolidation of IT and security responsibilities.

Full deep dive on the last mile of agentic security: https://t.co/nycfiTE2c1

[Frank Wang @ffwang2]

hiring talent is a lot like vc investing. the top firms get access to the best deals with high likely of high ROI. the other ones have to settle or find a diamond in the rough and take on more risk

[Frank Wang @ffwang2]

@0xAlcibiades @rauchg then a lot of companies are prob in a bad place

[Frank Wang @ffwang2]

@paulg agreed. what happens to the people leader CEOs who don't know how to build products, just orgs?

[Frank Wang @ffwang2]

@garrytan this is the best use of AI. but you've also wiped out huge a segment of security :P

[Frank Wang @ffwang2]

i like this take

[Can Vardar @icanvardar]

ai won’t replace builders it will expose people who were never really building anything in the first place

[Frank Wang @ffwang2]

@hetmehtaa have taste

[Frank Wang @ffwang2]

@gregisenberg probably AI generated

[Frank Wang @ffwang2]

@badcryptobitch @nikitabier that's true. the takes are better here, but we need to bring back hashtags

[Frank Wang @ffwang2]

Trying to block enterprise AI adoption is a losing battle. The real engineering challenge is building the guardrails to secure it in real-time. 🧵

Enter the AI Proxy.

But if you want to know if a tool in this space is legitimate or just agent-washed marketing fluff, look at how it handles the streaming token problem.

Traditional web proxies (like legacy CASBs or SWGs) inspect static HTTP payloads. They hold the request, scan the text, and pass it along. That architecture fails completely with LLMs. Developers expect instantaneous, millisecond-by-millisecond token streaming in their terminals and IDEs. If a security gateway adds even a 200ms hiccup to an autocomplete function, engineers will instantly find a workaround to disable it.

A real AI proxy has to process massive, high-volume concurrent requests and inspect data streams on the fly—evaluating context windows and masking secrets without breaking the connection.

This is exactly why owning your own global infrastructure is the ultimate moat. It’s why @Cloudflare and @Zscaler came to dominate the web gateway market—they understood that raw performance and low latency are the ultimate product features.

Right now, startups like @joinformal have a massive head start because they treat security teams like developers who want programmable, policy-as-code controls. But to survive the traffic load long-term, the next-gen players will have to migrate away from self-hosted models and build out their own distributed global infrastructure.

Full deep dive on why infrastructure is the defining moat for AI security: https://t.co/Y5rrYUgzEh

#Cybersecurity #Infosec #AIProxy #Cloudflare #Infrastructure #SecurityEngineering

[Frank Wang @ffwang2]

@ThePrimeagen probably bc it's just as good opus

[Frank Wang @ffwang2]

@badcryptobitch @nikitabier im going back to linkedin

[Frank Wang @ffwang2]

@badcryptobitch why! noooo

[solst/ICE of Astarte @IceSolst]

CYBER APOCALYPSE is real, but it’s caused by the # of sales people exceeding the # of security engineers

They’re selling products that don’t exist to teams that won’t use them

[Frank Wang @ffwang2]

The cybersecurity blank check has officially bounced. 📉. I discuss this more in my weekly newsletter, Frankly Speaking.

In our post-ZIRP reality, security teams are finally being forced to justify their existence as business units. The era of building top-heavy, bureaucratic empires to manage manual processes is over.

As AI engineering velocity explodes, the cybersecurity budget is undergoing a massive structural shift across three buckets:

1️⃣ Headcount Compression: We won't see massive, multi-layered security orgs anymore. The future belongs to flat teams of elite security generalists, essentially software engineers paid a premium to write automated defense loops. Human administrative waste is being swapped for raw token costs.

2️⃣ The Commoditization of Compute: Savvy buyers are rejecting massive SaaS markups from vendors who just wrap frontier models. As model costs plummet like AWS infrastructure, companies want to Bring Your Own Key (BYOK).

3️⃣ One-Shot Context Over Conversations: If your AI tool requires a security analyst to have a continuous back-and-forth conversation with a chatbot, it’s a chore, not a product. The winning vendors will be those providing the exact environmental context required for agents to operate autonomously and execute in a one-shot manner.

The future of security isn't about managing headcount but about empowering the outcome.

Full budget breakdown: https://t.co/LPhbTfNB6e

#Cybersecurity #AI #SecurityEngineering #TechBudgets #VentureCapital

[Frank Wang @ffwang2]

@techspence highly depends on the company. sometimes security people don’t want the power. that’s also the issue

[Frank Wang @ffwang2]

@Flomerboy also the issue is that companies don't need managers. they need leaders. nowadays if you need a manager, you've probably overhired, esp. in engineering

[Frank Wang @ffwang2]

@Flomerboy i think most people have had bad managers. i think your experience is probably atypical. also i think i've been given the wrong type of manager, which is a larger issue