Posted by Tanuj Dargan | June 23, 2025

Why I Started Leaning on AI for Technical Writing

I spend a lot of my week drafting release notes, README files, and tutorial walkthroughs. It’s rewarding—until I’m staring down a blank page at 11 p.m. After watching GPT demos turn bullet points into full paragraphs in seconds, I decided to test whether a language model could lighten the load without flattening my style or clarity. That kicked off a personal research project: How can technical writers keep rhetorical agency while collaborating with generative AI?

Step 1 | Clarify the Boundaries

I outlined three non-negotiables before firing up the AI:

  1. Voice checkpoint: Every draft must still sound like me—conversational, a tad nerdy, and never salesy.
  2. Fact firewall: The AI can suggest phrasing, but I fact-check every snippet, every code sample, every CLI flag.
  3. Attribution honesty: If a section is heavily AI-assisted, I note that in my change log.

Defining guardrails up front turned AI from a threat into a partner.

Step 2 | Behaviourist Drills—Turbocharged

Traditional behaviourist learning—repetition with feedback—shows up in the AI’s autocomplete prowess. When I type a heading like “Prerequisites”, GPT instantly suggests:

- Node.js ≄ 18  
- PostgreSQL 15  
- Yarn 4 or npm 10

Accepting (or tweaking) those snippets is faster than copy-pasting from old docs. The reinforcement loop? Each accepted suggestion improves the model’s next guess. I still do the work; I just do it at 2× speed.

Step 3 | Cognitivist Scaffolding—Mapping the Doc

The real win comes when I ask GPT to outline a document rather than write it. I’ll paste a high-level feature list and prompt:

“Create a logical doc structure that moves a reader from installation to first success in ≀ 10 steps.”

The resulting outline is rarely perfect, but it surfaces gaps in my mental model. By rearranging, merging, or deleting sections, I refine both the doc and my own cognitive map of the product.

Step 4 | Constructivist Co-authoring—Finding My Voice

When the outline is solid, I switch to a “pair-writer” workflow:

  1. Seed paragraph: I draft a rough first pass in my own words.
  2. AI revision: I ask GPT to tighten the prose, add examples, or simplify jargon.
  3. Human remix: I read aloud, inject personality, and ensure the tone still feels like Sam, not Skynet.

This back-and-forth mirrors pair programming: I keep agency, the AI accelerates iteration, and the document evolves through dialogue rather than dictation.

Pitfalls & Fixes

ChallengeHow I Mitigate
Voice drift (text suddenly sounds corporate)Keep a personal style guide handy; run “compare tone” prompts to align revisions.
Hallucinated commandsTest every CLI snippet in a sandbox VM before it hits the docs.
Over-relianceDraft at least one section completely solo to stay sharp.

What I’ve Learned About Agency

  • Tools amplify intent, not replace it. If I’m fuzzy on my audience, AI just produces fuzzy prose faster.
  • Reflection closes the loop. A quick meta-note—“Why did I accept this suggestion?”—helps me notice patterns in my own writing habits.
  • Transparency builds trust. Customers appreciate a footnote like: “This paragraph was generated with GPT-4 and reviewed by the docs team.” Nobody’s asked for a refund yet.

Final Thought

Generative AI is the most eager co-writer I’ve ever had—24/7, no coffee breaks—but I remain the editor-in-chief. By blending behaviourist speed boosts, cognitivist structuring, and constructivist ownership, I get the best of both worlds: faster drafts and a stronger authorial voice. The machine may suggest, but the final sentence is mine to approve—or delete.