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Writing Assistant ​

Writing a long-form article, blog post, or report usually means juggling multiple documents, losing context between sessions, and starting over when you pick it up again days later. Moltbot solves this by maintaining full context across conversations. Start an outline on Monday, refine section 3 on Wednesday, polish the conclusion on Friday — Moltbot remembers everything.

Prerequisites ​

  • Moltbot running and connected to Telegram
  • Memory system enabled — Cross-session context depends on memory. See Memory System
  • Browser/Fetch MCP tool (optional) — For researching source material during writing
  • File system MCP tool (optional) — For saving drafts to files

How It Works ​

Moltbot acts as a collaborative writing partner. You provide direction — topics, outlines, audience, tone — and Moltbot drafts, expands, edits, and refines. The key differentiator from a standalone AI chat is memory: Moltbot retains the full context of your writing project across multiple sessions without you having to repeat background information.

Setup ​

Step 1: Start a Writing Project ​

Kick off by providing the context:

You: I'm writing an article about self-hosted AI for technical
decision-makers. Outline: 1. Why self-host 2. Solution comparison
3. Cost analysis 4. Implementation path.
Expand section 3 with specific numbers and a comparison table.

Moltbot generates the expanded section and remembers the entire project context — the topic, audience, outline, and everything it has written so far.

Step 2: Continue Across Sessions ​

Come back hours or days later and pick up where you left off:

You: Let's continue the self-hosted AI article.
Rewrite the introduction to be more compelling.
Open with a provocative question.

You do not need to re-explain the article's topic, audience, or outline. Moltbot retrieves this from memory.

You: Now expand section 2 — solution comparison. Include
Ollama, vLLM, and llama.cpp. Add a table comparing
ease of setup, model support, and GPU requirements.

Step 3: Research and Incorporate Sources ​

If you have the browser tool configured, Moltbot can research while writing:

You: For the cost analysis section, search for current
GPU cloud pricing (AWS, GCP, Lambda Labs) and compare
with buying a dedicated RTX 4090 setup. Include real numbers.

Combine with saved reading material:

You: Check my reading notes for any articles about
self-hosting costs. Incorporate relevant data points
into section 3.

Step 4: Edit and Polish ​

Use Moltbot for targeted editing:

You: The conclusion feels weak. Rewrite it to end with
a clear call to action and a memorable closing line.
You: Review the full article for:
- Inconsistent terminology
- Sections that are too long or too short
- Claims that need citations
List the issues and suggest fixes.
You: Make the tone more conversational throughout.
It reads too much like a whitepaper right now.

Step 5: Save the Final Draft ​

Write the completed article to a file:

You: Save the complete article to ~/writing/self-hosted-ai-draft.md

Or output it in a specific format:

You: Format the article as a dev.to blog post with proper
markdown, including a header image suggestion and tags.

Common Writing Workflows ​

Brainstorming:

You: I want to write about developer productivity tools.
Give me 10 possible angles, rated by uniqueness and
potential reader interest.
You: I like angle 4 — "Why Most Developer Tools Fail."
Develop a full outline with section headers and
2-3 bullet points per section.

Rewriting for different audiences:

You: Take the self-hosted AI article and rewrite the
executive summary for a non-technical CTO audience.
Remove jargon, focus on business impact and cost savings.

Expanding from notes:

You: Here are my rough notes from the conference talk:
- LLMs are getting smaller and faster
- Edge deployment is becoming viable
- Privacy regulations driving self-hosting
- ROI breaks even at ~100k requests/month

Turn these into a 1500-word article with proper structure.

Collaborative drafting:

You: Here's my draft of paragraph 2:
"Self-hosting gives you control. You own the data, you own the model,
and you own the infrastructure. But it also means you own the problems."

Polish this. Keep the punch but improve the flow.

Generating supporting content:

You: For the article, generate:
1. A tweet thread (5 tweets) summarizing the key points
2. A LinkedIn post version (300 words)
3. Three possible titles for A/B testing

Edge Cases and Troubleshooting ​

  • Very long articles: If your article exceeds the LLM's context window (typically 100,000+ tokens for modern models), Moltbot may lose track of earlier sections. For book-length content, work section by section and ask Moltbot to save each section to memory explicitly.
  • Conflicting instructions: If you give contradictory editing instructions across sessions ("make it more technical" then later "make it more accessible"), Moltbot may struggle to reconcile them. Be explicit about which direction takes priority.
  • Factual accuracy: LLM-generated content may contain plausible-sounding but incorrect claims, especially for specific numbers, dates, or technical details. Always fact-check quantitative claims and technical specifics before publishing.
  • Voice consistency: If you write some sections yourself and let Moltbot write others, there may be subtle tone differences. Ask for a consistency pass: "Review the full article and smooth out any tonal shifts between sections."
  • Version control: Moltbot overwrites when it rewrites. If you want to compare versions, save drafts to different files or ask Moltbot to show a diff: "What did you change in the last revision?"

Pro Tips ​

  • Set the context once, write forever. At the start of a project, give Moltbot a comprehensive brief: audience, tone, word count target, key messages, what to avoid. Memory stores all of this, so you never repeat it.
  • Use Moltbot as an editor, not just a writer. Paste your own writing and ask for specific feedback: "Is the argument in paragraph 3 convincing? What's the weakest point?" AI feedback on human writing is often more useful than fully AI-generated content.
  • Build a style profile. Tell Moltbot about your writing preferences: "I prefer short sentences. I never use the word 'leverage.' I like concrete examples over abstract statements." Save this to SOUL.md for permanent application.
  • Research first, write second. Use the Read-It-Later recipe to save relevant articles, then ask Moltbot to synthesize them before writing: "Based on the 5 articles I saved about LLM benchmarks, what are the key themes I should cover?"
  • Iterate in small chunks. Rather than asking for a full 3,000-word article in one go, build it section by section. The output quality is higher when Moltbot focuses on 300-500 words at a time.
  • Schedule writing sessions. Use a Context-Aware Reminder: "Remind me at 8am tomorrow to continue the AI article. Include what section I was working on last."

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