Solo development with AI
In solo development with AI you do the work as three: you, the AI assistant in the IDE, and autonomous agents that iterate on things while you switch to another task. This mode has its own set of “blind spots”:
- Long-running autonomous tasks — an agent spends half an hour dealing with a DB migration, and you don’t want to check the terminal every 30 seconds.
- External dependencies — LLM APIs, vector DBs, embedding services: their status changes without warning, and you don’t have an SRE team.
- Cost — a lot of tokens are burned, it’s easy to lose control over the bill.
- Model quality — a new model release can break your pipeline right at night.
- MCP tools — if your AI talks to its MCP server, its downtime looks like “the model is acting dumb” rather than an alert.
Notifly covers all this in a few lines: heartbeats, active monitors, webhooks, and custom cloud functions for synthetic checks send a push to your device exactly when you need to intervene.
Ready-made recipes
Section titled “Ready-made recipes”| Scenario | What it covers |
|---|---|
| LLM API spend | Token budget overrun |
| LLM provider availability | OpenAI/Anthropic/etc. not responding, 5xx, rate limits |
| Model latency degradation | Unexpected “model became slower” |
| Long-running AI agent task completed | ”Agent finished refactoring — go review” |
| Stuck agent / loop | Heartbeat protection against silent hangs |
| Human-in-the-loop required | Agent paused a task — your approval is required |
| Vector DB / RAG infrastructure | Qdrant/Pinecone/Weaviate are down |
| Eval / model quality degradation | Regression after changing a prompt or model |
| Safety / prompt injection triggered | Suspicious user input |
| MCP server health | Own/third-party MCP stopped responding |
| Custom cloud function integrity check | A server-side “synthetic user” that sends an alert when something breaks |
Additional recipes
Section titled “Additional recipes”Cost and quotas
Section titled “Cost and quotas”Availability and latency
Section titled “Availability and latency”AI agents
Section titled “AI agents”Response quality
Section titled “Response quality”RAG and data
Section titled “RAG and data”Security
Section titled “Security”Infrastructure and development
Section titled “Infrastructure and development”- AI does PR review
- Flaky tests found
- Canary deployment errors
- Long DB migration progress
- Webhook retry storm
- Memory leak in serverless
- Mobile client crash
Personal
Section titled “Personal”Why push and not email
Section titled “Why push and not email”LLM incidents are often short and noisy: 10 minutes of 500s → fixed. Email alerts come in batches with delay and drown in the inbox; a push notification to your phone via Notifly is instantaneous, free, and easy to silently dismiss if you see the incident already resolved.
All recipes in this section use the same basic stack:
POST /message— ad-hoc alerts from code;- Heartbeat — “agent is alive”;
- Active monitors — external HTTP/TCP/TLS checks;
- Webhooks — receiving events from billing/CI;
- Email Inbox — alerts from providers who don’t have webhooks;
- custom cloud functions on YC — for your own checks.