Once your framework is set and your tone is chosen, length and variables are the fine-grained controls that sharpen output. Length sets how many sentences Wyra writes for each slot. Variables determine exactly what goes into specific parts of every message. Used together, they give you precision without sacrificing personalization.
Understanding length
Length sets sentences per slot — not a word count for the whole message.
The length scale runs from 1 (shortest) to 5 (longest), and each level sets how many sentences Wyra writes for every slot. For email: 1 is one sentence per slot, 2 is one to two, 3 is two to three, 4 is three to four, 5 is four to five. LinkedIn is compressed: 1 is one short sentence per slot, 2 is one, 3 is one to two, and 4 and 5 are both two. Total length is simply slots times sentences per slot, so there is no fixed word target and no hard cap — and Wyra doesn't pad short sentences to simulate depth. Level 1 is the tightest setting, not an unconstrained one.
Length previews your framework — it doesn't travel with the campaign
The length slider regenerates the messaging step's preview leads so you can see how your framework reads at different sentence depths. It's a calibration tool for writing better slots, not a setting that's carried into the full campaign send — once the campaign launches, every lead is generated at the default depth of one sentence per slot, on both channels, regardless of the length you previewed. A preview tuned at length 3 to 5 will come out noticeably shorter in the real send. If you need a ceiling that carries into the send, write it into the framework as a plain instruction, for example “Keep it under 120 words” — Wyra treats that as a hard limit and does not print it in the message. Otherwise, use the preview to tighten or loosen your slot instructions until the output looks right; that's what determines your actual send, not the length number itself.
1
Shortest
One sentence per slot (one short sentence on LinkedIn). The tightest setting, and the depth launched email campaigns use.
2
Compact
One to two sentences per slot on email, one on LinkedIn. Gets to the point fast.
3
Balanced
Two to three sentences per slot on email, one to two on LinkedIn. Enough room to build the case without excess.
4
Extended
Three to four sentences per slot on email, two on LinkedIn. Good for complex offerings or enterprise audiences.
5
Longest
Four to five sentences per slot on email. LinkedIn stays at two — the top two settings are the same there.
Wyra never drops a slot to hit a length
Every slot is filled, in order, at the sentence depth the length level sets — no slot is condensed away or skipped to make a message shorter. To shorten a message, remove slots or tighten the slot instructions themselves. More specific instructions produce tighter, more deliberate output at every length setting.
How length and slots interact
These two settings work together. Match them intentionally.
The total length of a message is determined by the combination of slot count and length setting — not either one alone. Here's how the combinations behave and when to use each. The five length dots behave differently per channel: on LinkedIn the top settings cap at two sentences per slot, so the “deep on a few points” combination below is an email pattern.
Few slots (2–3)
+ Short length (1–2)
Tight and punchy
Each slot produces one concise sentence. Total message stays short and direct.
LinkedIn, C-suite email, re-engagement
Many slots (5–6)
+ Long length (4–5)
Detailed and thorough
Every slot gets full expansion. Produces a complete, well-argued message with all dimensions of the offering covered.
Complex enterprise email, long-cycle deals
Many slots (5–6)
+ Short length (1–2)
Broad but compressed
Wyra covers all the slots but compresses each one tightly. You get the full structure without bulk — but some nuance gets lost.
When you need breadth but inbox context demands brevity
Few slots (2–3)
+ Long length (4–5)
Deep on a few points
Each slot gets significant expansion. Good when you want to dwell on one key insight or proof point rather than covering everything.
Challenger campaigns, single-insight openers
Length in practice
Same 3-slot framework. Same lead. Three different lengths.
Framework: {opener connecting to lead’s AWS partner context} · {pain point around co-sell pipeline velocity} · {CTA tied to MAP funding window}. Lead: VP of Partnerships at an AWS Advanced partner SI.
Length 1 — Shortest
“Advanced tier partners competing for PDM attention need pipeline moving fast. We help AWS SIs accelerate co-sell sourcing. MAP funding closes Q1 — worth 20 minutes?”
Length 3 — Balanced
“At the Advanced tier, co-sell velocity is everything — partners competing for PDM attention need pipeline building fast, not sitting in qualification queues. We help AWS SIs move from signal to co-sell motion in days rather than weeks, using ecosystem intelligence to prioritize the right opportunities at the right time. With MAP funding allocations Q1-weighted, now is the lowest-cost window to validate the approach. Worth 20 minutes to see how this works for a team your size?”
Length 5 — Longest
“At the AWS Advanced tier, the gap between partners who compound their co-sell motion and those who plateau usually comes down to one thing: pipeline velocity. When opportunities sit in qualification for weeks, PDMs move on. By the time a partner has an account mapped, the window has closed. We work with AWS SIs to solve that gap — using ecosystem intelligence to identify co-sell-ready accounts, generate tailored outreach automatically, and get opportunities into ACE before the conversation moves elsewhere. Teams using this approach have cut the time from signal to active co-sell by more than 60% and increased partner-sourced pipeline by an average of 40% within the first quarter. MAP funding allocations are Q1-weighted this year, which makes now the lowest-cost window to test this motion against your current approach. Would a 20-minute walkthrough of how this works for a team at your tier be worth your time before the window closes?”
Length 3 is a good starting point for calibrating most email frameworks
Start at length 3 and adjust from there while you're previewing. If the preview reads too long for your audience, move to 2. If the message feels thin and doesn't build enough of a case, move to 4 — then tighten or loosen your slot instructions until the preview reads the way you want at that size. Use the 3 preview leads to calibrate — look at the shortest and longest outputs, not just the first one. Remember the preview is the only place the length level applies; the launched campaign sends at length 1, so make sure the framework reads well there too.
Variables — three types
AI Descriptors, custom slots, and exact verbatim. Each serves a different purpose.
Variables give you precise control over what appears in specific parts of every message. You can use all three types in a single framework — Wyra handles them independently and combines them into a coherent message for each lead.
AI Descriptors — Wyra's pre-generated variables
When you open the messaging step, Wyra generates a set of short slot labels from your offering data — covering greetings, self-introductions, recipient insights, pain points, solutions, outcomes, proof points, cost of inaction, objections, and CTAs. For list-based campaigns they are generic rather than built from a single offering. Type { } in the framework and choose from the Select AI Variable list. The label you pick is inserted as a slot, not as finished text — Wyra fills it per lead at generation time.
AWS Partner example
Inserted as: {Short social proof with specific outcomes}
Fills per lead as: “40+ ISVs migrated to AWS-native architecture with 60% average reduction in infrastructure overhead”
SaaS example
Inserted as: {Opener on Recipient current outreach status quo}
Fills per lead as: “personalized outreach at PLG scale doesn't keep up with the volume teams need to hit targets”
Custom Slots — your own AI variable instructions
When Wyra's pre-generated descriptors don't match what you need, write your own. A custom slot is a curly-brace instruction {like this} placed anywhere in the framework. Wyra reads the instruction, draws from all available data — offering, lead profile, campaign context — and fills it in uniquely for every lead in the campaign. The more specific the instruction, the more precisely Wyra can execute it.
AWS Partner — specific slot
{lead’s current AWS partner tier and most recent co-sell or Marketplace activity}
Wyra finds and inserts the right data per lead — different for every prospect in the campaign
SaaS — specific slot
{lead’s company growth stage and the outreach challenge most common at that stage}
Wyra infers growth stage from company data and maps it to the most relevant pain point
Exact Verbatim — fixed text that appears in every message
Text you write directly into the framework — not inside curly braces — that you want to appear in every message exactly as written. Wyra copies it verbatim; it doesn't rewrite it or soften it, and normal sales language — urgency, bold claims, a strong CTA — isn't touched. Two exceptions: a plain writing instruction you type outside braces (for example “keep it under 120 words” or “mention their recent funding”) is followed, not printed; and profanity or text aimed at the AI itself is dropped from the output entirely. Everything else outside braces is copied word for word, so keep verbatim text focused on the message itself. Use it for branded phrases, specific product claims, compliance statements, or any language that must appear exactly as written.
AWS Partner example
Wyra is an AWS Select Tier Partner specializing in GTM acceleration for ISVs and SIs.
Appears in every message exactly as written — word-for-word
SaaS example
Wyra is SOC 2 Type II certified and GDPR compliant.
Fixed claim — appears word-for-word in every message in the campaign
Merge tags in the Greeting and Subject boxes
The Greeting and Subject boxes above the framework body accept {first_name}, {last_name}, {company} and {title}, swapped in per lead at send time — the default greeting is “Hi {first_name},”. Two editor rules apply to the framework body: every { must be closed (the editor warns on an unclosed brace, and Wyra drops that text from every message until it is), and the body needs at least 120 characters before Update is enabled.
Putting it together
A framework using all three variable types.
This framework combines AI descriptors, custom slots, and exact verbatim in a single 4-slot email for an AWS partner campaign.
Framework — 4 slots, mixed variable types
Offering: GTM Intelligence Platform. Lead: VP of Partnerships at AWS Advanced SI. Length: 3. Tone: Default.
Why mixing variable types works
Each type serves a different need in the same message. Custom slots give Wyra the flexibility to personalize deeply for each lead. AI descriptors handle the elements where Wyra's pre-built context is already strong — proof points, pain points, CTAs. Exact verbatim locks the parts that must stay fixed — brand claims, compliance statements, product names. Used together, they give you a message that's simultaneously personalized, contextually strong, and precisely controlled where it matters.
Common variable mistakes
Three things that consistently produce weak output.
Vague slot instructions
{pain point} gives Wyra too little to work with — it defaults to the most general version of a pain point. {pain point for a PLG team transitioning to sales-assisted at Series B} gives Wyra exactly the lens it needs.
Using verbatim for everything
Verbatim text doesn't personalize. A framework that's mostly verbatim produces messages that feel like templates. Reserve verbatim for claims that genuinely can't vary — let slots handle the personalization.
Ignoring AI descriptors
Wyra's pre-generated descriptors are built from your offering data — pain points, solutions, outcomes, proof points, and objections. They're often the fastest path to strong output. Review them before writing custom slots from scratch.
Mismatching slots and length
5 slots at length 1 gives you five one-sentence beats — the full structure, but each point stated once. 2 slots at length 5 gives you two slots at four to five sentences each — deep, but only on two points. Match slot count and length to your audience and channel.
Where to go next