Connor Florczyk

Founder @brieflywealth | The Context Engine for Financial Services | Ex-Morgan Stanley

[Connor Florczyk @Connor_Floor]

@SheTalksFinance What could it buy them though

[Connor Florczyk @Connor_Floor]

@cmsinvests Inflation will eat away at your spend

[Connor Florczyk @Connor_Floor]

@unusual_whales This makes sense because there’s more of them and birth rates have declined

[Connor Florczyk @Connor_Floor]

@ClaudeDevs Even this config can't stop Opus 5 from writing a paragraph for a yes or no anwser...

[Crémieux @cremieuxrecueil]

America is more unequal than many of its Western European peers, but even its lower middle class is well off compared to them.

Link: https://t.co/CwHKoiCMaW

[Xiaoyin Qu @quxiaoyin]

If you left your coding agent alone for more than 1h, don't hit continue. Open a new session.
Send the exact same message. While you're working, it costs 1x. After coffee, 1.3x. After a call, 1.6x.
After lunch: 13x.

The cache holding your session expires at exactly 60 minutes, and your first message has to rebuild the whole thing from scratch.

A new session costs 4.5x. So before you walk away: "summarize where we are." After lunch, paste it into a fresh window.

Measured across a month of my own Claude Code — 110 sessions, 46,580 turns.

[Connor Florczyk @Connor_Floor]

@dremnik What if you combined a bunch of these open-source projects into one repo, like an operating system for non-tech people?

[Connor Florczyk @Connor_Floor]

@cremieuxrecueil These models coming out clearly show more than pure distillation . You don't beat benchmarks by copying alone.

[Connor Florczyk @Connor_Floor]

@MTSlive Competition is good, these model providers need to figure out how to prevent distillation or double down on agentic work which is not as easy to copy

[Connor Florczyk @Connor_Floor]

@PimDeWitte This is what happens when you train on another model. Knowledge distillation happens across most LLMs.

[Ashwin Gopinath @ashwingop]

Claude Tag is a Trojan horse.  Not because Anthropic is doing anything evil. Because the incentives are obvious.

Day one, this looks like a great feature: tag Claude in Slack, let it follow the thread, remember context, connect to tools, break down tasks, chase work, and act like a teammate.

But that is exactly the problem. The moment your AI vendor becomes a shared coworker, it stops being just a model provider. It starts becoming the place where work is interpreted, remembered, routed, and eventually executed.

That is not model lock-in. That is context lock-in. You are now renting your company back from them.

Models can be swapped. Agents can be copied. But the memory of how your company actually works is much harder, maybe impossible, to move: the Slack scar tissue, the exception paths, the customer promises, the unfinished threads, the weird workflows, the implicit owners, the “we tried that in Q2 and it failed” knowledge.

Once that lives inside one vendor’s agent layer, you are not renting intelligence anymore. You are renting your company’s operating memory.

And the pricing model makes it even more dangerous. A human coworker has a salary. Claude has unbounded tokenized activity. The more work moves through it, the more the vendor captures not just IT spend, but labor spend.

This is the enterprise bargain people will regret: Convenience now, and rapid decent into dependency.

The right architecture is simple: rent the best intelligence from whoever is best this month. OpenAI, Anthropic, Gemini, open source, whatever. But own the context layer.

Your company memory should be inspectable, permissioned, portable, and model-neutral. It should not be buried inside the same vendor that sells you the intelligence and the workflow surface.

Claude Tag is useful. That is why it is dangerous. Rent the intelligence, but own the context. Or, regret later.

[Connor Florczyk @Connor_Floor]

@jenzhuscott MCP's will replace most Apps

[John Suh @john_ssuh]

Increasingly, I believe companies may need to be rebuilt from the ground up, where you have a single timeline of all observability + product metrics + file changes laid out in a retrievable system, like Datadog + Posthog + Google Drive + Slack (really unified filesystem of Claude Code chats + Codex chats). This might be the new data foundation for any and all companies to maximize AI. Needs to be rebuilt because keeping track of diffs on existing system basically impossible to produce longitudinal information on decisions and rollbacks, something coding agent storage companies are actively trying to figure out, but this should extend to businesses as a whole.

Highly skeptical existing businesses will adopt this though because it means overhauling everything about their instrumentation and business data, but I think businesses built on this foundation probably can execute 100x better and faster

[Connor Florczyk @Connor_Floor]

Feeling a big improvement going from Opus 4.7 to GPT 5.5

[Connor Florczyk @Connor_Floor]

@DOGE @USGSA @AnthropicAI OpenAI is getting further behind Anthropic every day

[big content guy @bigcontentguy]

big day for guys who like to monitor situations

[Connor Florczyk @Connor_Floor]

Your Brain Doesn't Have Enough RAM for This Job https://t.co/39HeKQ2rQC

[Connor Florczyk @Connor_Floor]

The Jobs AI Won’t Replace https://t.co/jHhCqnvz5U

[Connor Florczyk @Connor_Floor]

@SwiftYouTube_ Mario manningham

[Connor Florczyk @Connor_Floor]

@GhettoGronk Am I clinically insane for believing we’ll win these games?