@r0ck3t23 current frontier LLMs have context windows of only ~200k–1M tokens. A typical executable binary is millions to billions of bits (far more than any context window can hold). How do we envision getting past that limitation in such a short timeframe ?
Let’s unpack why the dual-agent approach in AI coding is a ticking time bomb for developers. Imagine Agent A meticulously building a robust function: clean, efficient, battle-tested against edge cases, integrating seamlessly with the codebase. Then Agent B, the “optimizer,” scans it and decides to rewrite from scratch. Boom: overwrites everywhere, turning solid code into a patchwork of conflicting logics, with Agent A undoing B’s changes in an endless loop.
This sparks a cascade of chaos. No coordination means vicious cycles of overrides, burned compute on redundancies, version control nightmares of tangled diffs, and Frankenstein code that barely runs. Devs waste time babysitting rogue AIs instead of shipping features, flipping a productivity tool into a black hole.
The core issue? It’s unrealistic beyond toy projects. In real-world dev, with looming deadlines and shifting requirements, unsupervised dual agents amplify chaos. Scaling to multi-agent systems? Pure drama, utterly unsustainable.
The fix: A shared “brain” for agents, a unified memory/knowledge base as the central hub. Agents reference past actions, cross-check in real time, align on goals, and build incrementally. No more torching code; just collaborative evolution that boosts human creativity.
Without it, we’re automating dev drama, not development. Who’s experimenting with shared memory frameworks? Share your war stories or ideas below, let’s evolve this!
we just raised another $25M after 10x'ing our ARR in 5 months. the crazy part is this almost never happened.
17 years ago, I watched Iron Man as a 10-year-old kid in Delhi. that night, I pulled my first all-nighter teaching myself to code. not because I wanted to build apps or make money.
because I wanted to build Jarvis.
my parents gave me 1 hour of screen time per day. so I coded in secret, sleeping every alternate night through middle school and high school. built 50+ apps. got a cease and desist from Google at age 12.
all for this one obsession: making computers understand us like humans do.
fast forward to today:
- we've raised $81M total to build the voice operating system
- growing revenue 40% month-over-month this year
- 70% user retention after one year (unheard of in consumer)
- teams at 270 of the Fortune 500 use Wispr Flow daily
our Series A2 was led by @hanstung at @notablecap (who was an early investor in five companies that made it to $100B valuation like Slack, Tiktok, and Airbnb). we also brought on @StevenBartlett as an investor and partner.
but here's what matters more than the money:
we cracked voice input. not transcription - actual understanding. our users hit "send" in under 0.5 seconds without checking. they trust it blindly. that's never existed before.
in a recent benchmark, Wispr came out as 3-4x more accurate than OpenAI, ElevenLabs, and Siri.
and we're just getting started. voice input was step one. now we're building the assistant that actually does things for you.
to my co-founder @SahajGarg6 - there's no one else I'd rather build Jarvis with than my college roommate and closest friend.
to our team pulling all-nighters and shipping magic - you're the reason that 10-year-old kid's dream is becoming real.
we're hiring cracked engineers and growth marketers who want to build the future of human-computer interaction.
the keyboard had a good 150-year run.
time to build what comes next.
PS: like, retweet, and bookmark to get wispr flow for free for 3 months ❤️
— Written with @WisprFlow