Subject: Make your own JEV
mongo-predict fills in missing fields from the documents you have…
Adopt the latest without rewiring
Switch models and providers per assistant. Classifiers like Jev are built in. Tonight's sorter is one.
LLMs help you build. Toolbelt helps you deploy, run and manage.
Nate McKervey, Apexti. Ninety seconds, then back to demos.
You argued about all of this this week.
- sub-agentsSingle loop or sub-agents? The real constraint turned out to be context size times turns.
- small modelsEnsembles of small models, Jev among them, beating a frontier model by 200 ms a call in production.
- secretsWhere do agent credentials live? Consensus: brokers, scoped tools, nothing destructive exposed.
- lock-inThe S-1 shows who pays the labs. How easy is it to switch, really?
- reliabilityNever trust an agent's "done." Re-run the check yourself.
Problem one
The best model changes every few weeks.
Switching means rewiring prompts, tools, evals and keys. So most teams stay on last quarter's model and pay for it.
Lab A
Lab B
Lab C
Open weights
Your stack, still wired to the one you picked in spring
Problem two
New building blocks keep landing.
Classifiers like Jev answer typed questions in about a tenth of a second with no chat turn. Using them means rethinking the flow, not swapping a model name.
40 list threads sorted tonight in 1.4 seconds, on Jev.
built something
asking for help
discussion
vendor pitch
~90 ms
Problem three
Your model vendor is paid by the token.
Nobody on that side of the table is paid to make you use fewer. Session logs a member shared this week: bounded sessions about 83k tokens a turn, long interactive ones about 396k.
Long interactive session~396k tokens a turn
Bounded, task-scoped~83k tokens a turn
Same work. Who is paid to get you to the second bar?
Problem four
Building it for one customer is a weekend. Running it for ten is a job.
Every customer brings their own logins, keys, data, model choices and bill. Deployments drift, spend surprises you, and every upgrade is ten upgrades.
Your build
Toolbelt by Apexti: the infrastructure layer for AI you run.
Paid to save you tokens
Code steps, classifiers, database storage and compression keep context small. Each customer's allowance is checked before every call.
A space per customer
Each gets its own logins, skills, memory, storage and plan. One screen for every customer's spend and usage.
Deployed and managed
From the domain to the databases. 2,000+ MCP connections, custom MCP servers in minutes, a pen-testing agent for review.
Least privilege you can see
Tools are hidden from the model, not just refused. Tonight's bot can read the list. It can't even see a send button.
Everything you saw tonight runs on it.
23
meetups in the archive
121
demos, searchable
1054
minutes of recordings you can ask about
40
list threads sorted on Jev
A bot in this call, the Hub, Ask MoM, the four-seat digest and a twice-weekly schedule. Built in about a day. Nothing to host.
Why it's different.
Model labs
Sell you tokens. Helping you use fewer isn't their job.
Workflow tools
You wire every step and redo it when the next model ships.
Toolbelt
Runs what you built, trims the tokens and keeps it current. Tell it what you want and it builds the flow and the interface.
LLMs help you build. Toolbelt helps you deploy, run and manage.
Build your next MoM demo on Toolbelt.
Want free credits to try it? Email me.
Start free, no credit card. apexti.com